Methods for and compositions for determining food item recommendations

ABSTRACT

Provided are methods and compositions for providing one or more food item recommendations for an individual. Methods can include determining an individual set of conditions from an overall set of conditions for the individual. Methods also include generating recommendations involving consumption of food, supplement and/or ingredients to affect the one or more biological conditions.

REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of the priority date of U.S.application 62/742,873, filed Oct. 8, 2018, and U.S. application62/834,284, filed Apr. 15, 2019, the contents of which are incorporatedby reference in their entirety.

BACKGROUND

Current methods of providing food and/or supplement recommendations areoften based on only one condition, and do not take into account multipleconditions that may be present in an individual, nor do they take intoaccount multiple effects of a given food on the conditions in theindividual. Improved methods and compositions for providing food and/orsupplement recommendations to an individual are needed.

SUMMARY

Provided herein is a method of determining recommendations ofdesirability of a plurality of different foods for an individual,wherein the individual has an individual set of biological conditionscomprising at least 1 biological condition, and wherein therecommendation for each food is based on its predicted effect on the atleast 1 biological condition. The individual set of biologicalconditions can comprises at least 2 biological conditions, and therecommendation for each food can be based on combining recommendationsfor the food for each of the two conditions. The individual set ofbiological conditions can comprise at least 3 biological conditions, andthe recommendation for each food can be based on combiningrecommendations for the food for each of the 3 conditions. Theindividual set of biological conditions can comprise at least 4biological conditions, and the recommendation for each food can be basedon combining recommendations for the food for each of the 4 conditions.The individual set of biological conditions can comprise at least 5biological conditions, and wherein the recommendation for each food isbased on combining recommendations for the food for each of the 5conditions. The condition or conditions can be determined from anoverall set of biological conditions. The plurality of different foodscan comprise at least 2, 5, 10, 20, 30, 40, 50, 70, 100, 120, 150, 170,200, 250, or 300 different foods. The recommendation of desirability ofthe plurality of different food can comprise at least 2, 3, or 4discrete values of desirability, wherein the values are in order ofdecreasing desirability. When more than one biological condition isexamined, if a recommendation of desirability of a food for any of thebiological conditions examined is different from the others, a finalrecommendation can determined by choosing the most restrictiverecommendation. In certain cases, the individual set of biologicalconditions comprises at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 biologicalconditions, and the recommendation for each food can based on itspredicted effect on at least some of the biological conditions in theindividual set of biological conditions, for example, the recommendationfor each food can be based on its predicted effect on at least ¼, ½, or¾ of the biological conditions in the individual set of biologicalconditions. The individual can be determined to have an individual setof biological conditions based on phenotype and microbiome informationfor the individual. The phenotype information can be obtained in aprocess comprising determining responses for the individual to aquestionnaire. The microbiome information can be obtained from a samplefrom the individual, such as a stool sample. The microbiome informationcan comprises transcriptome information. The microbiome information cancomprise information regarding viruses in the microbiome. The method caninclude determining a recommendation for desirability of consumption ofa first food of the plurality of foods for the individual comprisesperforming at least one of (i) predicting an effect of macronutrientcontent of the first food on a first biological condition in theindividual and determining a first recommendation based on the predictedeffect of macronutrient content of the food; (ii) predicting an effectof one or more specific compounds in the first food on the firstbiological condition in the individual and determining a secondrecommendation based on the predicted effect of the one or more specificcompounds; and (iii) predicting an effect of the first food on amicrobiome of the individual, and determining a third recommendationbased on the predicted effect on the microbiome. In certain embodiments,the method comprises performing at least two of steps (i)-(iii). Incertain embodiments the method comprises performing all of steps(i)-(iii); in some cases, steps (i), (ii), and (iii) are performed insequential order. In certain embodiments of the method, after a food isgiven a first recommendation after step (i), then step (ii) is performedand the food is given a second recommendation, wherein the secondrecommendation can be the same as the first recommendation or an upgradeor downgrade of the first recommendation, then step (iii) is performedand the food is given a third recommendation, wherein the thirdrecommendation can be the same as the second recommendation or anupgrade or downgrade of the second recommendation. In certainembodiments, desirability for consumption of a food can have at least 2,3, or 4 values, which can be graded in terms of desirability. The methodcan further comprise performing one or more of steps (i)-(iii) for asecond biological condition, where the second biological condition isdifferent from the first, and determining a recommendation fordesirability of consumption of the food for the second biologicalcondition. At least one of steps (i)-(iii) can be performed for thesecond biological condition. At least two of steps (i)-(iii) can beperformed for the second biological condition. At least one of steps(i)-(iii) is performed for the second biological condition, which insome cases can be performed sequentially. The method can furthercomprise combining the recommendations for desirability of consumptionof the food for the first biological condition and for the secondbiological condition to determine a combined desirability forconsumption of the food; in certain cases, the combining comprisesdetermining whether one recommendation for desirability is morerestrictive than the other, and, if so, determining that the combineddesirability for consumption of the food is the more restrictivedesirability. The method can further comprise performing one or more ofsteps (i)-(iii) for a third biological condition, where the thirdbiological condition is different from the first and second biologicalconditions, and determining a recommendation for desirability ofconsumption of the food for the third biological condition. At least oneof steps (i)-(iii) can be performed for the third biological condition.At least two of steps (i)-(iii) can be performed for the thirdbiological condition. All three of steps (i)-(iii) can be performed forthe third biological condition; in certain embodiments the steps areperformed sequentially. The method can further comprise combining therecommendations for desirability of consumption of the food for thefirst, second, and third biological conditions to determine a combineddesirability for consumption of the food. The method can furthercomprise determining which if any, of the recommendations fordesirability of consumption of the food is most restrictive, and, if so,determining that the combined desirability for consumption of the foodis the most restrictive desirability. The method can further comprisingperforming steps (i)-(iii) for a fourth biological condition, where thefourth biological condition is different from the first, second, andthird biological conditions, and determining a recommendation fordesirability of consumption of the food for the fourth biologicalcondition. In certain embodiments, at least one of steps (i)-(iii) isperformed for the fourth biological condition. In certain embodiments,at least two of steps (i)-(iii) is performed for the fourth biologicalcondition. In certain embodiments, all three of steps (i)-(iii) isperformed for the fourth biological condition; in certain embodiments,steps (i)-(iii) are performed sequentially. The method may furthercomprise combining the recommendations for desirability of consumptionof the food for the first, second, third, and fourth biologicalconditions to determine a combined desirability for consumption of thefood, for example determining which if any, of the recommendations fordesirability of consumption of the food is most restrictive, and, if so,determining that the combined desirability for consumption of the foodis the most restrictive desirability. In certain embodiments, any of theabove methods may further be used to determine a recommendation fordesirability of consumption of a second food from the plurality offoods, wherein the second food is different from the first, and wherethe method comprises performing one or more of steps (i)-(iii) for thesecond food, for at least 1, 2, 3, 4, or 5 biological conditions fromthe individual set of biological conditions. For any of the methodsabove, one or more of steps (i)-(iii) are performed for at least 2, 5,10, 20, 50, 100, 150, 200, 250, or 300 different foods. For any of themethods above, one or more of the foods are classed as part of a foodgroup and the prediction of one or more of steps (i), (ii) and/or (iii)is based on the food group. The method may further comprise providing anexplanation for the recommendations for at least some of the foods tothe individual, where the explanation is determined from results of oneor more steps of analysis of the food and its effect or effects on oneor more conditions of the individual; the recommendation can be providedas text suitable for understanding by a layman.

Provided herein is a method of determining a set of food recommendationsfor an individual comprising (i) determining an individual set of one ormore biological conditions for the individual from an overall set ofbiological conditions by combining phenotype and microbiome informationfor the individual; and (ii) determining the food recommendations forthe individual based on the predicted effects of foods and/or foodgroups on one or more of the conditions for the individual. Themicrobiome information can include transcriptome information. Themicrobiome information can include taxa information and gene expressioninformation. The microbiome information can include one, two, three,four or all of bacterial, virus information, archaebacteria, or protestinformation. The predicted effects can comprise macronutrient effects,specific compound effects, microbiome effects, or any combinationthereof. If predicted effects of a food or food group lead to differentrecommendations for a food for different conditions, the mostrestrictive recommendation can be chosen as the final recommendation.

Provided herein is a method of determining a recommendation fordesirability of consumption of a first food for an individual comprisingperforming at least one of (i) predicting an effect of macronutrientcontent of the first food on a first biological condition in theindividual and determining a first recommendation based on the predictedeffect of macronutrient content of the food; (ii) predicting an effectof specific compound content of the first food on the first biologicalcondition in the individual and determining a second recommendationbased on the predicted effect, wherein the second recommendation can bethe same as or different from the first recommendation, depending on themicronutrient effect; and (iii) predicting an effect of the first foodon a microbiome of the individual, and determining a thirdrecommendation based on the predicted effect, wherein the thirdrecommendation can be the same as or different from the secondrecommendation, depending on the microbiome effect. The microbiomeinformation can include information regarding the presence or absence,quantity, or other characteristic of one, two, three, four, or all ofbacteria, viruses, archaebacteria, fungi, or protists that may beaffected by the first food. The method can comprise performing at leasttwo of steps (i)-(iii). The method can comprise performing all of steps(i)-(iii), for example, performing steps (i), (ii), and (iii) insequential order. The recommendation for desirability for consumption ofa food can have at least 2, 3, or 4 values, which can be graded in termsof desirability. The method can further comprise performing one, two, orall of steps (i)-(iii) for a second biological condition, where thesecond biological condition is different from the first, and determininga recommendation for desirability of consumption of the food for thesecond biological condition. The recommendation for desirability ofconsumption of the food for the first biological condition can becompared to that for the second biological condition to determine which,if either, is more restrictive, and determining a final recommendationfor desirability of the food that is the more restrictive desirability.The method can further comprise performing one, two, or all of steps(i)-(iii) for a third biological condition, where the third biologicalcondition is different from the first and second biological conditions,and determining a recommendation for desirability of consumption of thefood for the third biological condition. The recommendations fordesirability of consumption of the food for the first, second, and thirdbiological conditions can be compared to determine which, if any, ismost restrictive, and determining a final recommendation fordesirability of the food that is the most restrictive desirability. Themethod can further comprise performing one, two, or all of steps(i)-(iii) for a fourth biological condition, where the fourth biologicalcondition is different from the first, second, and third biologicalconditions, and determining a recommendation for desirability ofconsumption of the food for the fourth biological condition. Therecommendations for desirability of consumption of the food for thefirst, second, third, and fourth biological conditions can be comparedto determine which, if any, is most restrictive, and determining a finalrecommendation for desirability of the food that is the most restrictivedesirability. The method can further comprise performing one, two, orall of steps (i)-(iii) for a fifth biological condition, where the fifthbiological condition is different from the first, second, third, andfourth biological conditions, and determining a recommendation fordesirability of consumption of the food for the fifth biologicalcondition. The recommendations for desirability of consumption of thefood for the first, second, third, fourth, and fifth biologicalconditions can be compared to determine which, if any, is mostrestrictive, and a final recommendation for desirability of the food canbe determined that is the most restrictive desirability. The method canfurther comprise determining a recommendation for desirability ofconsumption of a second food, wherein the second food is different fromthe first, by performing one, two, or all steps (i)-(iii) for the secondfood, for the first, second, third, fourth, or fifth condition, or anycombination thereof, and combining recommendations for differentconditions if the recommendations differ. In any of the methods of thisparagraph, one, two, or all of steps (i)-(iii) can be performed for atleast 2, 5, 10, 20, 50, 100, 150, 200, 250, or 300 different foods. Inany of the methods of this paragraph, a food can be classed as part of afood group and the prediction of (i), (ii) and/or (iii) can be based onthe food group. For any of the methods of this paragraph, the method canfurther comprise providing an explanation for the recommendations for atleast some of the foods to the individual, wherein the recommendation isdetermined from results of one or more steps of analysis of the food andits effect on one or more conditions of the individual. The explanationcan be provided as text suitable to layman understanding.

Provided herein is a composition comprising a list of foodrecommendations for an individual, wherein the recommendations arederived from predicting effects of each food on the list on one or morebiological conditions of the individual, wherein the effects compriseone, two, or all of effects of macronutrient content of the food,effects of specific compound effect of the food, and effects of the foodon the microbiome of the individual with regard to at least onebiological condition of the individual. The list can further comprise,for at least some of the foods, an explanation for the recommendationfor the food, wherein the recommendation indicates one or more probableeffects of macronutrient and/or specific compound content of the foodand/or microbiome interaction with the food, on one or more of thebiological conditions, or the effects of one or more conditions, in theindividual. The explanation can be in layman's terms. The list cancomprise at least 5, 10, 15, 20, 25, 30, 40, 50, 70, 100, 150, 200, 250,or 300 different food recommendations. Each food on the list can bedesignated a value according to its desirability for the individual,such as one of at least 2, 3, or 4 values for desirability, for exampleone of values for desirability. In certain embodiments, the foods arechosen from the foods in Table 2.

Provided herein is a method of improving one or more biologicalconditions in an individual comprising (i) supplying the individual withfood, supplement and/or ingredient recommendations, wherein the food,supplement and/or ingredient recommendations are based predicted effectsof one or both of macronutrient content, specific compound content ofthe food or supplement on one or more biological conditions of theindividual and, optionally, effect of the food on a microbiome of theindividual; and (ii) altering the individual's food, supplement and/oringredient consumption so that it more closely matches the food,supplement and/or ingredient recommendations. The one or more biologicalconditions of the individual can be determined by analysis of phenotypeinformation and microbiome information from the individual. Phenotypeinformation can be obtained in a process comprising determiningresponses for the individual to a questionnaire and microbiomeinformation is obtained from a sample from the individual, such as astool sample. The microbiome information can comprise transcriptomicinformation. The microbiome information can comprise taxonomicinformation and gene expression information. The microbiome informationcan comprise information regarding one or more biochemical molecules ina sample from the individual. The one or more biochemical molecule canbe informative of one or more biochemical activities. The information onbiochemical activity can be obtained by a process comprising quantifyingan enzymatic activity assay, a growth-inhibition culture, metabolicprofiling, or any combination thereof. In certain embodiments, thebiochemical molecule is a small molecule, and the small molecule cancomprise a metabolite generated by the biochemical activity. The smallmolecule can comprise a short-chain fatty acid, such as butyrate orpropionate. The small molecule can comprise a substrate of thebiochemical activity. The food recommendations can comprise a list offoods, each of which has a designation indicating desirability orundesirability of that food for the individual. The designation can haveone of at least 2, 3, or 4 values. The food, supplement and/oringredient recommendations can be produced by a process comprising (i)selecting an individual set of biological conditions for the individualfrom an overall set of biological conditions based on the individual'sphenotype and microbiome information; (ii) determining overall predicteddesirability of foods, food groups, and/or supplements on at least partof the individual set of biological conditions for the individual; and(iii) from the results of (ii) determine the food, supplement and/oringredient recommendations for the individual. The method can furthercomprise gathering information from the individual regarding phenotypeand microbiome after the individual has implemented the recommendationsfor a period of time, such as one week to one year. After gather theinformation after the period of time, the method can further comprisealtering the food, supplement and/or ingredient recommendations for theindividual based on the phenotype and microbiome information gatheredafter the period of time.

In one aspect provided herein is a method comprising: (a) generating-omic data from a subject; (b) determining, from the -omic data, thepresence of one or more biological conditions in the subject; (c)accessing a knowledge base, wherein the knowledge base indicates, foreach of a plurality of items selected from foods, supplements andingredients, a desirability rating of consuming the item for the one ormore biological conditions; and (d) for each item, implementing computerlogic to determine a final recommendation for the item, wherein thefinal recommendation is based on the combined desirability ratings forthe biological conditions. In one embodiment the subject is a human. Inanother embodiment the -omic data is generated from a biological samplefrom the subject. In another embodiment the biological sample comprisesa gut microbiome sample or a blood sample. In another embodimentgenerating -omic data comprises performing high-throughput sequencing onnucleic acids from a sample from the subject to produce sequence data.In another embodiment the functional activity conditions are determinedfrom functional activity scores determined from the -omic data. Inanother embodiment the functional activity scores are integrative scorescomprising more than one type of input data, e. G., KO identifiers,taxonomy identifiers or human gene identifiers. In another embodimentthe functional activity scores are non-integrative scores comprisingonly one type of input data. In another embodiment the -omic datacomprises gut microbiome metatranscriptomic data. In another embodimentthe biological conditions comprise functional activity conditions. Inanother embodiment the functional activity conditions include or moreof: butyrate production pathways, LPS biosynthesis pathways, methane gasproduction pathways, sulfide gas production pathways, flagellar assemblypathways, ammonia production pathways, putrescine production pathways,oxalate metabolism pathways, uric acid production pathways, salt stresspathways, biofilm chemotaxis in virulence pathways, TMA productionpathways, primary bile acid pathways, secondary bile acid pathways,acetate pathways, propionate pathways, branched chain amino acidpathways, long chain fatty acid metabolism pathways, long chaincarbohydrate metabolic pathways, cadaverine production pathways,tryptophan pathways, starch metabolism pathways, fucose metabolismpathways, inflammatory activity, metabolic fitness, digestiveefficiency, intestinal barrier health, protein fermentation, gasproduction, microbial richness, detoxification potential (ability ofmicrobiome to detoxify the body), gut neuro-balance (impact ofmicrobiome on the brain, e.g., by production of neurotransmitters),neurological health, cardiovascular health, hormonal balance,musculoskeletal health, hepatic function, urogenital health,mitochondrial activity, immune function, gastrointestinal health,diabetes, skin conditions, infectious disease, stress response,mitochondrial health, mitochondrial biogenesis, oxidative stress, agingand senescence. In another embodiment the -omic data comprisesmetatranscriptomic data, and determining functional activity conditionscomprises executing computer logic to determine functional activityscores from the metatranscriptomic data. In another embodimentdetermining comprises: (i) executing computer logic to determinebiological pathway scores and taxa activity scores, and (ii) derivingfunctional activity scores from the biological pathway scores and taxaactivity scores. In another embodiment determining biological pathwayscores comprises determining activity of functional orthologs (e.g., ina KEGG Orthology). In another embodiment functional activity scores aremeasured as continuous variables or in categories. In another embodimenta functional activity score outside of a reference range or outside oneor more reference categories indicates a functional activity condition.In another embodiment the -omic data comprises phenotypic data used todetermine phenotypic conditions. In another embodiment the -omic datacomprises both metatranscriptomic data and phenotypic data. In anotherembodiment the -omic data comprises proteomic, which data is used todetermine functional activity conditions. In another embodiment thebiological conditions includes at least one condition selected from theconditions of Table 1. In another embodiment a plurality of items in theknowledge base are foods selected from the foods of Table 2. In anotherembodiment a plurality of items in the knowledge base are supplementsselected from the supplements of Table 3. In another embodiment aplurality of items in the knowledge base are ingredients selected fromthe compounds of Table 4. In another embodiment the desirability ratingsfor foods comprise a plurality of ratings hierarchically arranged fromleast desirable to consume for the condition to most desirable toconsume for the biological condition. In another embodiment theplurality of desirability ratings is four ratings, wherein two ratingsare undesirable ratings (e.g., “avoid” and “minimize”, one rating ishighly desirable (e.g., “indulge” or “superfood”) and another rating isdesirable or neutral (e.g., “enjoy”). In another embodiment thedesirability ratings for supplements or ingredients comprise a positiverecommendation or no recommendation. In another embodiment a pluralityof the desirability ratings are based on literature sources and expertcuration. In another embodiment the logic determines a finalrecommendation by prioritizing, first, ratings indicating a negativeeffect of the item on a condition, and, prioritizing second, ratingsindicating a most beneficial effect of the item on a condition. Inanother embodiment the hierarchy of rating, from least to mostbeneficial, is 1-4, and the priority of ratings to produce a finalrecommendation for a plurality of the items is 1>2>4>3 (e.g.,“avoid”>“minimize”>“superfood”>“enjoy”). In another embodiment themethod further comprises determining from the -omic data, a predictedglycemic response by the subject to each of one or more items in theknowledge base, which response indicates a glycemic responsedesirability rating; and incorporating the glycemic responsedesirability rating in determining the final recommendation for theitem. In another embodiment the glycemic response desirability rating iseither positive or negative. In another embodiment the method furthercomprises determining whether the subject has a sensitivity (i.e., anadverse reaction) for an item; and incorporating any adverse reaction indetermining the final recommendation for the item.

In another aspect provided herein is a method comprising: (a) generatingfunctional activity scores by: (i) obtaining a gut microbiome samplefrom a subject; (ii) sequencing nucleic acids from the sample to producesequence data; (iii) determining from the sequence data, (1) gene (e.g.,KEGG Orthology) activity scores; and (2) taxa activity scores; (iv)determining from the gene activity scores and the taxa activity scores,a functional activity score for each of a plurality of functionalcategories; (b) optionally, generating a glycemic response score foreach of a plurality of food items selected from foods, supplements andingredients by: (i) executing logic that determines a glycemic responsescore for a subject based on macronutrient content of the food and thesubject's gene activity scores and taxa activity scores; (c) optionally,determining food sensitivities in the subject; (d) generating phenotypescores by: (i) obtaining phenotype data from the subject; (ii)determining, from the phenotype data, a phenotype score for each of aplurality of phenotype categories; (d) accessing from computer memory afood database that includes, for each food item and each sub-optimalfunctional activity and phenotype status, a hierarchical recommendationof the food or supplement; (e) generating an overall hierarchicalrecommendation for each food or supplement based on combinedrecommendations of a food for each sub-optimal condition present and,optionally, the predicted glycemic response and/or food sensitivity tothe food or supplement.

In another aspect provided herein is a method comprising: a) receiving abiological sample from a subject; b) sequencing nucleic acids frombiological sample to produce nucleic acid sequence data; c) collectingphenotypic data from the subject; d) determining phenotypic conditionsin the subject from the phenotypic data and functional activityconditions in the subject from the nucleic acid sequence data; e)accessing a knowledge base that includes for each of a plurality of fooditems desirability ranking of the food for each of the phenotypicconditions and functional activity conditions present in the subject; f)using a recommendation engine, executing logic to produce arecommendation for each food item for the subject; and f) outputting thefood recommendations to an electronic device accessible by the subject.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

The following references, which may be relevant to the presentdisclosure, are incorporated herein by reference: WO 2019/113563; WO2018/237209; WO 2019/099574; WO 2018/160899; PCT/US2019/028590.PCT/US2019/050102; U.S. Provisional application 62/804,737

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an approach for personalizing food and supplementrecommendations for a subject.

FIG. 2 shows an exemplary algorithm for determining the presence orabsence of biological conditions from -omic data collected from thesubject. Raw questionnaire data can include symptoms in anthropometricsand or drugs/supplements being taken by the subject. This data issubject to phenotype data scoring. Scores are used to infer the presenceor absence of phenotype conditions. Raw next generation sequencing (NGS)meta-transcriptomics data is processed by bioinformatics to identifyexpressed genes (e.g., KO's) and active microbes. This data is subjectto the functional activity scoring. Functional activity scores are usedto infer the presence or absence of functional activity conditions.

FIG. 3 shows development of a functional activity score for a high-levelhealth metric, in this example, digestive efficiency. The functionalactivity is a composite of functional activity scores for a number oflower order functional categories. In this example, functionalcategories include protein fermentation, motility/gases, intestinalbarrier health and SIBO-like/hypo-HCL pattern. Intestinal barrierhealth, in turn, is a composite of still further lower order functionalcategories including pro-inflammatory and anti-inflammatory components.In this example, scores for each of the intermediate functionalcategories in the hierarchy are based on both biochemical pathwayactivity (pathway component) and active taxa (taxa component).

FIG. 4 shows an exemplary application of recommendation engine thatapplies logic as described herein to produce final recommendations forfoods.

FIG. 5 shows an exemplary flow chart for generating and outputting foodrecommendations for a subject. The recommendations are based onphenotypic and/or functional activity conditions of the subjectdetermined from phenotypic and nucleic acid sequence data, and processedby logic executed by a recommendation engine.

DETAILED DESCRIPTION

Provided herein are methods and compositions to provide food, supplementand/or ingredient recommendations to an individual. Also provided hereinare methods and compositions to determine an individual set ofbiological conditions for an individual from an overall set ofbiological conditions. In certain embodiments food recommendations forthe individual are based on predicting the effect of foods and/or groupson one or more biological conditions of an individual. In addition,provided herein are methods and compositions of improving one or morebiological conditions of an individual by supplying the individual withfood, supplement and/or ingredient recommendations, where the food,supplement and/or ingredient recommendations are based on phenotype andmicrobiome information for the individual, and altering the individual'sfood, supplement and/or ingredient intake based on the food and/orsupplement recommendations.

I. Definitions

Unless defined otherwise, all terms of art, notations and othertechnical and scientific terms or terminology used herein are intendedto have the same meaning as is commonly understood by one of ordinaryskill in the art to which the claimed subject matter pertains. In somecases, terms with commonly understood meanings are defined herein forclarity and/or for ready reference, and the inclusion of suchdefinitions herein should not necessarily be construed to represent asubstantial difference over what is generally understood in the art.

The section headings used herein are for organizational purposes onlyand are not to be construed as limiting the subject matter described.

II. Introduction

Provided herein are methods of making personalized food, supplementand/or ingredient (sometimes collectively referred to as “food items” or“items”) recommendations (herein, “food recommendations”) for a subject.Food recommendations provide a beneficial ranking of each food orsupplement for the subject based on biological conditions present in thesubject and, optionally, based on the subject's predicted glycemicresponse to the food and/or the subject's sensitivity to the food. Thefinal recommendation classifies the food according to its effect on thebiological conditions, collectively. Rankings are typicallyhierarchical, from least to most beneficial for the subject to consume.In one model, there are four rankings, including two negative rankingsand two positive rankings (or two negative rankings, a neutral rankingand a positive ranking).

Referring to FIG. 1, -omic information is collected for an individual(101). This can include Phenomic (105) and Metatranscriptomic (110)data. Analysis of phenomic data can indicate the presence of phenotypicconditions (125). Bioinformatics can be used to transformmetatranscriptomic data into functional activity scores (131).Functional activity scores that are determined to be outside a referencerange indicate the presence of a functional activity condition (120).Based on phenotypic conditions and functional activity conditions in thesubject, a knowledgebase of foods and conditions (130) is accessed. Inaddition, subject glycemic response to foods (140) and subject foodsensitivities (150) also are determined. A computerized recommendationengine (160) then analyses item desirability rankings for all conditionspresent in the subject and, optionally, the subject's glycemic responseto the item and any subject sensitivity to the item. Using logic, therecommendation engine determines an overall, or final recommendation(Food Recommendation (170)) concerning the food items for the subject.

Biological conditions in a subject include any detectable condition,including, without limitation, phenotypic conditions and functionalactivity conditions. Phenotypic conditions are based on outwardphenotype and subjective responses by the subject, obtained, for exampleby questionnaire. Functional activity conditions are conditions in whicha functional activity score for a functional category are determined tobe outside a reference range, e.g., suboptimal. Determination of afunctional activity condition can be based on biochemical informationcollected from the subject. Biochemical data can include data from thesubject's microbiome, in particular, from the transcriptome of themicrobiome. Transcriptome data can be divided into two parts,biochemical pathway activity data and microbial taxa activity data. Inother embodiments, biochemical data can include information from thehuman transcriptome. Biochemical pathway activity data indicates theactivity level of various biochemical pathways in the microbes. Taxaactivity data indicates the quantity of various active taxa in the gutmicrobiome, but their activity levels. These data are, in turn, analyzedto provide a functional activity score to various higher-levelfunctional activities in the subject that involve a plurality ofpathways and taxa, such as inflammatory activity.

Predicted glycemic response to a food by a subject also can becalculated based on changes in blood sugar levels by a subject afterconsumption of a food or supplement.

Sensitivity of a subject to a food or supplement, e.g., allergy, (“foodsensitivity”) also can be determined by self-reporting from the subjector by testing, e.g., by skin testing.

The food recommendation engine makes use of a food database. The fooddatabase includes a table of foods and supplements. For each biologicalcondition, each food or supplement is ranked (e.g., given arecommendation), according the effect consumption of the food orsupplement has on the biological condition (e.g., a positiveeffect=ameliorates the condition, or a negative effect=worsens thecondition). Again, rankings can be provided as a number from low tohigh, such as 1-4, or by a descriptor, such as “avoid” or “indulge”.

Effect of a food item on a subject (that is, beneficial or detrimentaleffect) (which is reported as a food recommendation) is a function ofthe collective rankings of the food item on each biological conditionthat the subject has, as optionally modified by glycemic response andfood sensitivity data. Accordingly, for a given subject, rankings of agiven food on biological conditions present in the subject, optionally,as well as predicted glycemic response and/or food sensitivity, are usedto generate the overall recommendation for the food for the subject.Various functions to generate the overall recommendation can be used.For example, the function could make hierarchical recommendations, inwhich a food or supplement ranked at a certain level for any biologicalcondition trumps all other rankings for the condition. In one such afunction, the presence of a single most negative rank (e.g., “avoid”)for any present biological condition would give the food a most negative(“avoid”) recommendation. If no food has a most negative rank for anycondition present, the presence of a single less negative rank (e.g.,“minimize”) for any present biological condition would give the food aless negative (e.g., somewhat negative) (“minimize”) recommendation. Ifno food has a most negative or less negative rank for any conditionpresent, the presence of a single most positive rank (e.g., “superfood”or “indulge”) for any present biological condition would give the food amost positive (“superfood”) recommendation. If no food has any of theaforementioned ranks, a neutral or mildly positive rank (e.g., “enjoy”)is assigned to the food for the subject. These rankings can be informedby predicted glycemic response and/or food sensitivity. For example, ahigh glycemic response (which is a negative response) would cap therecommendation to no better than a negative or less negative ranking,while a low glycemic response (which is a positive response) would notalter the recommendation based on condition ranking, or would increasethe ranking by a rank. Similarly, presence of a sensitivity to a foodcould result in a veto, automatically ranking the food at the leastbeneficial level.

III. Biological conditions

Typically, the methods and compositions described herein utilizeinformation regarding one or more biological conditions for anindividual. An individual may be a member of a species of a mammal, aspecies of a rodent, a species of a mouse, a species of a rat, a speciesof a dog, a species of a cat, a species of a hamster, a species of amonkey, a species of a pig, a species of a squirrel, a species a guineapig, a species of a gerbil, a species of a bird, a species of a hydra, aspecies of a rabbit, a species of a fish, a species of a frog, a speciesof a cow, a species of a lamb, a species of a chicken, a species ofDrosophila, a species of Xenopus, a species of horse, and a human. Incertain embodiments, the individual is a human.

Biological conditions refer generally to the presence of any suboptimalor pathologic health or wellness condition. A phenotype condition isdetermined to be present when phenotypic data, alone or in combination,indicates the condition. A functional activity condition is determinedto be present when a functional activity score is determined to besuboptimal.

Data used in the creation of the recommendations described hereintypically comprise large data sets including thousands, tens ofthousands, hundreds of thousands or millions of individual measurementstaken from or about a subject, typically at the systems biology level.The data can be derived from one or more (typically a plurality)different biological system components. These biological systemcomponents, also referred to herein as “feature groups”, include,without limitation, the genome (genomic), the epigenome (epigenomic),the transcriptome (transcriptomic), the proteome (proteomic), themetabolome (metabolomic), the organismal cellular lipid components(lipidome), organismal sugar components of complex carbohydrates(glycomic), the proteome and/or genome of the immune system (immunomics)component of a system, organism phenotype (phenome, phenomic,phenotypic) and environmental exposure (exposome). (Generally referredto herein as “-omic” data or information.)

Biological conditions discussed herein may be determined by any suitablemeans. In certain embodiments, biological conditions are determined from-omic data, including any of the feature groups discussed above. Incertain embodiments the -omic data comprises phenotype and/or microbiomeinformation. Alternatively, the-omic data can include proteomic data. Anindividual set of biological conditions for an individual may be chosenfrom an overall set of biological conditions, based on phenotype and/ormicrobiome information for the individual. Exemplary biologicalconditions are shown in TABLE 1.

TABLE 1 Exemplary Biological conditions Abdominal Weight Acne AttentionDeficit Disorder Allergy Allergy ENT Condition Allergy Lung ConditionAllergy Skin Condition Anxiety Autoimmune Autoimmune Gut ConditionAutoimmune Joint Condition Autoimmune Skin Condition CardiovascularCondition Depression Diverticular Condition Dysbiosis DysGlycemia(hyperglycemia) Dysmotility ENT Condition Eye Condition Female HormoneCondition Food Reaction GERD GI Inflammation Headache ConditionHypoGlycemia HypoThyroid Condition Infection Condition Insomnia LeakyGut Condition Liver Condition Lung Condition Male Hormone ConditionMuscle Condition Nerve Condition Nutritional Deficiency Obese OverweightSmall Intestinal Bacterial Overgrowth Thyroid Condition

Provided herein are methods and compositions for determining a set ofbiological conditions for an individual. The individual set ofbiological conditions can be determined based on combined phenotype andmicrobiome information for the individual, and can include at least 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or more than 15conditions. The process of determining an individual's set of biologicalconditions may include determining which conditions from an overall setof biological conditions the individual has; the overall set ofbiological conditions can be any suitable set, and can include at least1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 20, 25, 30, 35 ormore than 35 conditions. An exemplary overall set of biologicalconditions is provided in TABLE 1.

A. Phenotype Information

Methods and compositions herein can utilize phenotype information for anindividual. Any suitable method of determining phenotype information forthe individual may be used. Exemplary methods include examination ofphysical or medical records, one or more interviews with the individualand/or others, examination of the individual, and use of questionnaires.

In certain embodiments, one or more questionnaires are used, whereresponses to the one or more questionnaires for the individual are usedto partially or completely determine phenotype information for theindividual, in particular, as related to biological conditions, forexample biological conditions in an overall set of conditions. Thequestionnaire or questionnaires may include any suitable number ofqueries, for example, at least 5, 10, 15, 20, 25, 30, 35, 40, 45, 50,55, 60, 65, 70, or over 70 questions. Responses to questions can beopen-ended (e.g., the individual may provide a written response to aquestion without limit to content of the response, such as a writtenanswer to a question such as “What are your health goals?”), questionswith specific answers (e.g., “what medications do you take,” “what isyour hip circumference in inches” and the like) or questions where theanswer can be selected from a limited number of options, or acombination. Limited option questions include yes/no questions,true/false questions, questions that require selection of one or moreresponse from a limited number of responses, which can be non-numericalresponses (e.g., “what is your ethnicity,” with responses limited to“American Indian or Alaskan Native,” “Southeast Asian,” “South Asian,”“Asian,” “Black or African American,” “ Native Hawaiian or other PacificIslander,” “Caucasian/White,” “Hispanic or Latino,” or “Other”) ornumerical responses (e.g., “How many cups of coffee do you drink eachday,” with responses limited to 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10+; or“how often have you been bothered by a certain symptom (such asheadache, or fatigue, or pain or aches in joints, etc.) in the past fourweeks,” with the answers limited to “none,” “a little,” or “a lot,”etc.), or any other suitable question type that provides informationuseful in determining a biological condition.

Any suitable method of determining phenotype information from responsesto the questionnaire(s), in particular, information regarding anindividual set of biological conditions for an individual, may be used.For example, a first biological condition may be assessed by examiningthe responses to a first subset of questions in the questionnaire(s);the questions in a subset may be weighted so that answers to somequestions count more than others. Specific responses to individualquestions in the first subset may be assigned specific numerical values,which can be adjusted according to the weight of the question, then thenumerical values for all responses in the first subset are totaled togive a phenotype score for the first biological condition. A similarprocedure may be followed to assess a second, different biologicalcondition in the individual, using a second subset of questions in thequestionnaire(s) to provide a phenotype score for the second biologicalcondition; the second subset of questions may be the same as ordifferent from the first subset. The process may be repeated for anysuitable number of biological conditions; when biological conditions foran individual are determined from an overall set of biologicalconditions, the upper limit will, of course, be the number of biologicalconditions in the overall set (or fewer, if some of the biologicalconditions in the overall set are mutually exclusive). Thus, the processcan be repeated for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 17, 20,22, 25, 30, or 35 conditions, to produce the same number of phenotypescores; each different biological condition is assessed with referenceto responses to its own specific subset of questions, which may be thesame as or different from subsets for other biological conditions.Questions may belong to more than one subset for more than onebiological condition, or may belong to only one subset.

Phenotypic information can be obtained, for example, from subjectresponses to questionnaires, or from a chat bot that interacts with thesubject through natural language conversations. Such questionnaires maygather information on traits such as age, sex, weight, blood type,headaches, faintness, dizziness, insomnia, watery or itchy eyes,swollen, red or sticky eyelids, bags or dark circles under eyes, blurredor tunnel vision (not including near or far-sightedness), itchy ears,earaches, ear infections, drainage from ear, ringing in ears, hearingloss, stuffy nose, sinus problems, hay fever, sneezing attacks,excessive mucus formation, chronic coughing, gagging, need to clearthroat, sore throat, hoarseness, loss of voice, swollen or discoloredtongue, gums or lips, canker sores, acne, hives, rashes, dry skin, hairloss, flushing, hot flashes, excessive sweating, irregular or skippedheartbeat, rapid or pounding heartbeat, chest pain, chest congestion,asthma, bronchitis, shortness of breath, difficulty breathing, bloatedfeeling, nausea, vomiting, diarrhea, constipation, belching, passinggas, heartburn, intestinal/stomach pain, pain or aches in joints,arthritis, stiffness or limitation of movement, pain or aches inmuscles, feeling of weakness or tiredness, binge eating/drinking,craving certain foods, excessive weight, compulsive eating, waterretention, underweight, fatigue, sluggishness, apathy, lethargy,hyperactivity, restlessness, poor memory, confusion, poor comprehension,poor concentration, poor physical coordination, difficulty in makingdecisions, stuttering or stammering, slurred speech, learningdisabilities, poor physical coordination or clumsiness, numbness ortingling in hands or feet, mood swings, anxiety, fear or nervousness,anger, irritability or aggressiveness, sadness or depression, frequentillness such as colds, frequent or urgent urination, genital itch ordischarge, decreased libido and PMS. Phenotypic information can becollected all in a single session, in several sessions involving a smallnumber of questions at each session, and over weeks, months or years,creating a ‘longitudinal’ view of the subject's phenotype. Each of thesecan be a biological condition.

Functional categories also include categories that may contribute tomore general categories, such as wellness, stress, anxiety, allergies,autoimmune condition, leaky gut, insulin resistance, metabolic syndrome,metabolic type, insomnia and, skin conditions.

Typically, determining the presence or absence of a condition and/ordegree of the condition, also requires microbiome information for theindividual, but in some cases phenotype information may be sufficient todetermine presence or absence and/or degree of a biological condition inthe individual. In these cases, to determine presence or absence of thecondition, the phenotype score for the biological condition may becompared to a threshold value, and if the phenotype score is above thethreshold value, or above or equal to the threshold value (or below thethreshold value or below or equal to the threshold value, depending onthe biological condition), then the biological condition is present, ifnot, it is not. Additionally, or alternatively, the biological conditionmay be assessed by assigning a degree to the condition, depending on thetotal phenotype score for the condition. Any suitable method ofassigning degree may be used, such as quartiles, quintiles, percentage,and the like.

B. Transcriptomic Information

Data can include information about microbes in the subject's microbiome,e.g., gut microbiome or from the subject's blood transcriptome. To theextent the data includes information from a plurality of differentorganisms in the microbiome, the data can be classified as meta-data,such as meta-genomic, meta-transcriptomic, meta-metabolomic,meta-proteomic and meta-epigenetic.

Data can also include phenotypic information about a subject, that is,information about objectively and/or subjectively measurable traits fora subject. Data can include lifestyle information about a subjectincluding, for example, diet, exercise, stress, alcohol use, drug use,supplement use, and sleep patterns. Data also can include biomic, e.g.,environmental, information about a subject including, for example,exposure to toxins, climate, external temperature, social interactions,location, work environment, hydration, activity level, and the like.

Methods and compositions herein can utilize microbiome information foran individual. Any suitable method of determining microbiome informationfor the individual may be used.

Microbiome can include gut, skin, mouth, nasal, vaginal and othermicrobial populations associated with an individual. In certainembodiments, information regarding the gut microbiome is used. Amicrobiome generally comprises heterogeneous microbial populations.Microbial communities are often made up of mixed populations oforganisms, including unknown species in unknown abundances. Microbialcomponents of the microbiome can include bacteria, archaebacteria,viruses, fungi, and protists. In some cases, information regarding one,two, three, four, or all of bacteria, archaebacteria, viruses, fungi,and protists can be used. In some cases, information regarding bacteriaand viruses is used.

Microbiome information can be obtained in any suitable way, typically byanalysis of one or more samples from the individual. Depending on themicrobial populations of interest, any suitable sample or samples may beused. Exemplary samples include earwax, sweat, breast milk, hair, blood,bile, cerebrospinal fluid, lymphatic fluid, semen, vaginal discharge,menstrual fluid, feces (stool), sputum, urine, saliva, secretions fromopen wounds, secretions from the eye, skin tissue (e.g., a skin biopsy),subcutaneous tissue, muscle tissue, adipose tissue, and a combinationthereof. Furthermore, a sample may be obtained from, for example, thegut, the vagina, the penis, a testicle, the cervix, the respiratorysystem, the ear, the skin, the rectum, the kidney, the liver, thespleen, the lung, the pancreas, the small intestine, the gallbladder,the lymph nodes, the colon, a nasal passage, the central nervous system,an oral cavity, a sinus, a nostril, the urogenital tract, an udder, anauditory canal, a breast, an open wound, the eye, fat, muscle, andcombinations thereof In certain embodiments, one or more stool samplesfrom the individual is used to determine microbiome information for theindividual.

Microbiome information useful in the methods and compositions discussedherein includes information regarding microbial taxa, such as genera,species and/or strains of the microbiome, e.g., gut microbiome asdetermined from one or more samples such as one or more fecal samples,such as species identities and/or quantities and/or relative quantities.Microbial information can also include expression information forvarious genes, indicating levels of transcription of various genes ofthe microbial species. Microbial information can also includebiochemical information, such as information regarding small moleculesproduced by the microbial species of the microbiome.

1. Information from Nucleic Acids

Polynucleotides can be extracted directly from the sample, or cells inthe sample can first be lysed to release their polynucleotides. In onemethod, lysing cells comprises bead beating (e.g., with zirconiumbeads). In another method, ultrasonic lysis is used. Such a step may notbe necessary for isolating cell-free nucleic acids.

Nucleic acids can be isolated from the sample by any means known in theart. Polynucleotides can be isolated from a sample by contacting thesample with a solid support comprising moieties that bind nucleic acids,e.g., a silica surface. For example, the solid support can be a columncomprising silica or can comprise paramagnetic silica beads. Aftercapturing nucleic acids in a sample, the beads can be immobilized with amagnet and impurities removed. In another method, nucleic acids can beisolated using cellulose or polyethylene glycol.

If the target polynucleotide is RNA, the sample can be exposed to anagent that degrades DNA, for example, a DNase. Commercially availableDNase preparations include, for example, DNase I (Sigma-Aldrich), TurboDNA-free (ThermoFisher) or RNase-Free DNase (Qiagen). Also, a QiagenRNeasy kit can be used to purify RNA.

Alternatively, or in addition, a sample comprising DNA and RNA can beexposed to a low pH, for example, pH below pH 5, below pH 4 or below pH3. At such pH, DNA is more subject to degradation than RNA.

If the target polynucleotide is RNA, the sample can be reversetranscribed into DNA. Reverse transcription generally takes place aftera sample has been depleted of DNA.

In some aspects, a sample can be depleted of nucleic acids and nucleicacid species that are abundant relative to other nucleic acids in thesample. Some of the abundant nucleic acids may not be target nucleicacids (e.g., they may not encode sequence signatures or may not beinformative of desired taxonomic information). The presence of theseabundant nucleic acids can reduce the sensitivity of some of the methodsdescribed herein. This can be true, for example, if target orinformative nucleic acids are rare relative to the abundant nucleicacids. Therefore, it can be advantageous to enrich a sample for targetsequences by removing non-informative abundant sequences. Examples ofsequences that can be removed include microbial ribosomal RNA, including16S rRNA, 5S rRNA, and 23S rRNA. Other examples of sequences that can beremoved include host RNA. Examples include host rRNA, such as 18S rRNA,5S rRNA, and 28S rRNA.

As used herein, the term “non-informative RNA” refers to a form ofnon-target or non-analyte species of RNA. Non-informative RNA speciescan include one or more of: human ribosomal RNA (rRNA), human transferRNA (tRNA), microbial rRNA, and microbial tRNA. Non-informative RNAspecies can further comprise one or more of the most abundant mRNAspecies in a sample, for example, hemoglobin and myoglobin in a bloodsample.

Methods of enriching nucleic acid samples include the use ofoligonucleotide probes. Such probes can be used for either positiveselection or negative selection. Such methods often reduce the amount ofnon-target nucleotides.

If the target polynucleotide is DNA, then DNA can be isolated withsilica, cellulose, or other types of surfaces, e.g., Ampure SPRI beads.Kits for such procedures are commercially available from, e.g., Promega(Madison, Wis.) or Qiagen (Venlo, Netherlands).

The isolated nucleic acids are generally sequenced for subsequentanalysis. The methods described herein generally employ high throughputsequencing methods. As used herein, the term “high throughputsequencing” refers to the simultaneous or near simultaneous sequencingof thousands of nucleic acid molecules. High throughput sequencing issometimes referred to as “next generation sequencing” or “massivelyparallel sequencing.” Platforms for high throughput sequencing include,without limitation, massively parallel signature sequencing (MPSS),Polony sequencing, 454 pyrosequencing, Illumina (Solexa) sequencing,SOLiD sequencing, Ion Torrent semiconductor sequencing, DNA nanoballsequencing, Heliscope single molecule sequencing, single molecule realtime (SMRT) sequencing (PacBio), and nanopore DNA sequencing (e.g.,Oxford Nanopore).

2. Transcriptome Sequence Preprocessing

Also provided herein are methods of analyzing RNA transcripts in aheterogeneous microbial sample. The RNA transcripts can be part of atranscriptome for a cell or cells in the heterogeneous microbial sample.Information regarding the transcriptomes of a plurality of cells fromdifferent species may be obtained. The methods generally includeisolating and sequencing the RNA found in a sample as described above.

The sequences obtained from these methods can be preprocessed prior toanalysis. If the methods include sequencing a transcriptome, thetranscriptome can be preprocessed prior to analysis. In one method,sequence reads for which there is paired end sequence data are selected.Alternatively, or in addition, sequence reads that align to a referencegenome of the host are removed from the collection. This produces a setof host-free transcriptome sequences. Alternatively, or in addition,sequence reads that encode non-target nucleotides can be removed priorto analysis. As described above, non-target nucleotides include thosethat are over-represented in a sample or non-informative of taxonomicinformation. Removing sequence reads that encode such non-targetnucleotides can improve performance of the systems, methods, anddatabases described herein by limiting the sequence signature databaseto open reading frames can the size of the database, the amount ofmemory required to run the sequence signature generation analysis, thenumber of CPU cycles required to run the sequence signature generationanalysis, the amount of storage required to store the database, theamount of time needed to compare sample sequences to the database, thenumber of alignments that must be performed to identify sequencesignatures in a sample, the amount of memory required to run thesequence signature sample analysis, the number of CPU cycles required torun the sequence signature sample analysis, etc.

In certain embodiments, quantitative measures of gene activity andmicrobial taxa are determined using the transcriptome of a microbiome ofthe subject. The transcript on includes RNA that is transcribed fromcells in a sample, in particular, microbial cells. In certainembodiments transcriptome analyzed comprises or consists essentially ofmessenger RNA, in particular, microbial mRNA. In certain embodimentsnon-informative RNA is removed from the transcriptome before analysis.In particular, ribosomal RNA can be removed from the transcriptome.Accordingly, taxonomic analysis can be performed on mRNA rather thanrRNA.

3. Taxonomic Identification

A) Paired End Alignment

To determine the identity of one or more organisms present in a sampleat a specific taxonomic level, paired-end (or optionally single)transcriptome reads from that sample are aligned to the library oftaxonomic signatures as described herein at that specific taxonomiclevel. Sequences can be aligned using, for example, the BWA aligner withthe mem algorithm. (Li H. (2013) “Aligning sequence reads, clonesequences and assembly contigs with BWA-,” arXiv:1303.3997v1[q-bio.GN].) BWA is often run with a minimal seed alignment length of 30nt, but other BWA parameters such as the mis-match penalty can bemodulated, as can downstream filters. Global thresholds for sensitivityand specificity can be tuned at this level by modulating the BWAparameters during model training after taxonomic signature generation ontest data sets of known composition. These values can then be appliedduring the identification step. The best unique alignment of a read orread pair to a unique genome signature at a specific taxonomic levelidentifies that taxonomic member as being present. Some organisms willbe identified to the strain taxonomic level while others may only beidentified to the genus level (or higher) depending on the nature ofdistinct sequences available in the database to make an accuratedetermination. In some aspects, a microorganism or a taxon is identifiedas being present in the sample if at least 1, 2, 3, 4, 5, 6, 7, 8, 9,10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100 or more sequencesignatures corresponding to the taxon are detected in the sample. Insome aspects, a microorganism or a taxon is identified as being presentin the sample if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30,35, 40, 45, 50, 60, 70, 80, 90, 100 or more sequence reads are detectedfor a sequence signature in the sample. In some aspects, a read isdetermined to match a sequence signature if the read is at least 90%,95%, 96%, 97%, 98%, 99%, 99.5%, 99.9% or 100% identical to at least aportion of the sequence signature or the entire sequence signature. Insome aspects, a read is determined to match a sequence signature if thesequence signature is at least 90%, 95%, 96%, 97%, 98%, 99%, 99.5%,99.9% or 100% identical to at least a portion of the read or the entireread. In a preferred embodiment, calling or identifying a microorganismas being present at one or more taxonomic levels requires at least 25reads of at least 100 nucleotide and a mismatch rate no greater than 2%when aligned against the curated database/library of unique genomesignatures.

Alternatively, or in addition, the methods, systems and databases hereincan be used to identify a biochemical activity present in the sample. Insome embodiments, the methods include aligning sequencing reads to adatabase comprising open reading frame information that is associatedwith a particular biological, e.g., biochemical, activity or pathway, asdescribed above. Some of such methods can include identifying taxonomicinformation for a sequence. Examples include the GOTTCHA algorithm,which detects sequence signatures that identify nucleic acids asoriginating from organisms at various taxonomic levels. Nucleic AcidsRes. 2015 May 26; 43(10): e69. Other methods include MetaPh1An, Bowtie2,mOTUs, Kraken, and BLAST. Some of such methods do not includeidentifying taxonomic information for the sequence, but instead mayidentify the biological activity, pathway, protein, functional RNA,product, or metabolite associated with a particular sequence read orsequence signature.

b) Use of Flanking Sequences

In another embodiment, transcriptome sequences that align to one portionof the unique genome signature database/library but do not align tosequences flanking the first portion in that alignment are eliminated.

In one version of this embodiment, identification of organisms on aparticular taxonomic member at a taxonomic level can be determined bymaking use of sequences that flank sequences in the taxonomic signature.That is, the method can make use of sequences of the genome removed fromthe genome in the generation of the taxonomic signature. In this methodtranscriptome sequences are often first aligned to the taxonomicsignature sequences. Then, portions of the aligned transcriptomesequences that do not, themselves, align with the signature sequencescan be compared to the sequences that flank the signature sequences. Ifthere is insufficient homology between these flanking sequences, theentire sequence read can be removed from the alignment protocol. Theminimum level of homology required for a sequence to remain in alignmentcan be, for example, at least 90%, at least 95%, at least 98%, at least99% or 100%.

c) Microorganism Quantitation

The methods, systems, and databases described herein can also be used toquantify a characteristic in a heterogeneous sample. In one aspect,provided herein are methods for quantifying microorganisms in a sample.Alternatively, or in addition, provided herein are methods forquantifying a particular biochemical activity associated with aheterogeneous microbial sample or a microorganism contained therein.Transcriptome sequences from the sample can be mapped to the ORF librarydescribed above. In some aspects, ORF library can be used to infertaxonomic information about the organisms present in the sample.Alternatively, or in addition, sequences that map to the library can beannotated to indicate information such as gene identity and genefunction.

Quantification of abundance can be done by computer by summing up thenon-overlapping length of profiles found for a taxonomic member (LinearLength or L), then determining the read coverage across that length(Linear Depth of Coverage or DOC). In some aspects, the non-overlappinglength is or comprises a sequence signature informative of taxonomicinformation.

Normalizing over the sum of all DOCs for a specific taxonomic levelallows one to arrive at the relative abundance (RA) of that taxonomicmember. In one embodiment, normalization comprises: determining thenumber of base pairs contained in a particular ORF, determining anaverage depth of coverage for the entire length of the ORF using thenumber nucleotides contained in sequence reads corresponding to the ORFand the length of the ORF, and determining the proportion of allsequence reads that correspond to the ORF.

Normalization can comprise determining an average depth of coverage forORFs identified in the sequencing data, summing the averages to generatea total depth of coverage, and dividing the depth of coverage for an ORFof interest by the total depth of coverage. Such a method can be used todetermine a relative amount or proportion of sequence reads for thetarget ORF in the sequencing data. Such methods can also account for therelative differences in lengths of ORFs, allowing for more directcomparisons, because the methods can use the depth of coverage for anORF rather than the total number of bases read. Thus, a number of basereads in a 1,000 bp ORF would have half the total depth of coveragecompared to the same number of base reads in a 500 bp ORF. The relativeamount or proportion of the ORF in the sample can be used to infer therelative activity of the target ORF.

In some aspects, the amount or relative amount can be compared to areference value. Examples of a reference value include a normal valueand a cutoff value that is a specified distance from a normal value(e.g., in units of standard deviation). The reference value may bedetermined from a different sample from the same subject (e.g., when thesubject was known to be healthy or prior to administration of the food,supplement, or medication). The reference value may also be determinedfrom one or more samples from other healthy subjects. The referencevalue may be an absolute or relative value. The reference value fordifferent biological conditions may be different for the same microbialentity, e.g., species.

The measure of gene expression at each taxonomic level can be calculatedbased on the Reads Per Kilobase (RPK) of transcript per Million mappedreads. Additional filters can be applied at this step on read count, L,DOC, or RA with thresholds determined during the model training step.Note this relative abundance will be for the DNA or RNA fraction of thattaxonomic member in the sample at time of library prep. If the sourcewas RNA, then the relative abundance calculated can correspond to therelative activity of that organism in the sample (e.g., gene expressionlevels). Alternatively, or in addition, if the source was RNA, then therelative abundance calculated for an ORF can correspond to the relativeactivity of that ORF, including the activity or pathway. If the sourcewas DNA, one relates to relative abundance of that organism assuming asingle genome copy per organism. The taxonomic relative activity can bequantified by finding the median or mode of non-zero Reads Per Kilobase(RPK) of transcript per Million mapped reads (RPKM values) and inversingscaling by the fraction of active genes.

The output of this process can be a report that indicates for a subjectsample the taxa of microorganisms in the sample. If the taxonomicidentity of the sample cannot be identified at a particular taxonomiclevel the report can indicate the intensity at the next highesttaxonomic level. The report can also indicate quantitative informationabout the sample this can include, for example, the relative amounts ofdifferent microorganisms in the sample. It can also indicate relativeactivity of microorganisms in the sample based on relative geneexpression. This can include, for example, types of genes that areeither expressed in high amounts or alternatively, in low amounts.Alternatively, or in addition, the report can indicate the identity andrelative amounts of biochemical activities in the sample. The report canindicate changes as to biochemical activity in the sample over time,such as during a time course. The report can indicate differencesbetween samples, including samples collected from the same source atdifferent times. The source can be a subject, including a human subject.

In some aspects, limiting the sequence signature database to openreading frames can reduce the size of the database, the amount of memoryrequired to run the sequence signature generation analysis, the numberof CPU cycles required to run the sequence signature generationanalysis, the amount of storage required to store the database, theamount of time needed to compare sample sequences to the database, thenumber of alignments that must be performed to identify sequencesignatures in a sample, the amount of memory required to run thesequence signature sample analysis, the number of CPU cycles required torun the sequence signature sample analysis, etc.

Reports can sometimes be output to paper, a screen, or a database.Reports can also be stored for later analysis or viewing. Reports can besent to third parties, such as subjects, healthcare professionals,customers, collaborators, etc.

As part of assessing the microbiome, one or more biochemical activitiesmay be assessed. The assessment may include one or more of quantifyingan enzymatic activity assay, a growth-inhibition culture, metabolicprofiling, quantifying one or more biochemical molecules, or anycombination thereof. Of particular interest are short chain fatty acids,for example butyrate and propionate. In certain embodiments, levels ofbutyrate are assessed and included in the microbiome information.

In certain embodiments a microbiome score for a biological condition,similar to a phenotype score, is assigned to the individual. The scoremay be obtained by any suitable method.

Typically, determining the presence or absence of a condition and/ordegree of the condition, also requires phenotype information for theindividual, but in some cases microbiome information may be sufficientto determine presence or absence and/or degree of a biological conditionin the individual. In these cases, to determine presence or absence ofthe condition, the microbiome score for the biological condition may becompared to a threshold value, and if the microbiome score is above thethreshold value, or above or equal to the threshold value (or below thethreshold value or below or equal to the threshold value, depending onthe biological condition), then the biological condition is present, ifnot, it is not. Additionally, or alternatively, the biological conditionmay be assessed by assigning a degree to the condition, depending on thetotal microbiome score for the condition. Any suitable method ofassigning degree may be used, such as quartiles, quintiles, percentage,and the like.

In certain embodiments, for a biological condition the phenotype scoreand the microbiome score may be combined, either with or withoutweighting each of the scores, to produce a combined score. Any suitablemethod may be used to combine the scores, such as simple addition. Thecombined score can then be used to determine presence or absence and/ordegree of a biological condition in the individual. In these cases, todetermine presence or absence of the condition, the combined score forthe biological condition may be compared to a threshold value, and ifthe combined score is above the threshold value, or above or equal tothe threshold value (or below the threshold value or below or equal tothe threshold value, depending on the biological condition), then thebiological condition is present, if not, it is not. Additionally, oralternatively, the biological condition may be assessed by assigning adegree to the condition, depending on the total combined score for thecondition. Any suitable method of assigning degree may be used, such asquartiles, quintiles, percentage, and the like.

4. Gene Activity Quantitation

The methods, systems and databases herein can be used to identifyactivity of a gene or a biochemical pathway present in the sample. Insome embodiments, the methods include aligning sequencing reads to adatabase comprising open reading frame information that is associatedwith a particular biochemical activity or pathway, as described above.Some of such methods can include identifying taxonomic information for asequence. Examples include the VIOMEGA algorithm (see WO 2018/160899(Vuyisich et al.) or GOTTCHA algorithm, which detects sequencesignatures that identify nucleic acids as originating from organisms atvarious taxonomic levels. Nucleic Acids Res. 2015 May 26; 43(10): e69.Other methods include MetaPh1An, Bowtie2, mOTUs, Kraken, and BLAST. Someof such methods do not include identifying taxonomic information for thesequence, but instead may identify the biochemical activity, pathway,protein, functional RNA, product, or metabolite associated with aparticular sequence read or sequence signature.

“Gene activity” or “activity of a gene” is a generally a function oftranscription, e.g., the quantity of RNA in a sample encoding the gene.This can be done at any taxonomic level. For example, gene activitycould be a measure of activity of the gene in a single species, or itcould be activity of the gene across organisms belonging to a commongenus, class, order or phylum. The term “gene” can refer to orthologs ofa gene across different species. Such orthologs can be identified, forexample, with the KEGG or theology.

C. Functional Activities And Functional Activity Scores

Functional activities are biological activity categories includingbiological or health functions or conditions at the cellular, organ ororganismal level. Functional activities are assigned functional activityscores based on such data. Functional activity scores representquantitative measures of functional activity. A functional category caninvolve any function related to health or wellness. Functionalcategories can embrace health parameters, health indicators, healthconditions and health risks. The activity of the function is assessed byanalyzing -omic, e.g., transcriptomic data, which is collected fromactive, living organisms, e.g., expressing RNA from their genomes.

Functional activity includes integrative functional activities andnon-integrative functional activities. Nonintegrative functionalactivities are based on a single type of data or function, such asmicrobiome pathway activity data, taxa group activity data and hosttranscriptomic data. Integrative functional activities are based on anbe based on a plurality of different kinds of data or functions. Forexample, such functional activities can combine pathway activity data intaxa activity data.

A) Pathways

In certain embodiments, functional activities include the activities ofone or more pathways. As used herein, the term “pathways” refers tobiological pathways, which are sequences of proven molecular events(such as enzymatic reactions or signal transduction or transport ofsubstances or morphological structure changes) that lead to specificfunctional outcomes (such as secretion of substances, sporulation,biofilm formation, motility). Many biological pathways are known in theart, and examples can be found on the web atwikipathways.org/index.php/WikiPathways, pathwaycommons.org, andproteinlounge.com/Pathway/Pathways.aspx. Manual expert curation ofscientific literature also can be used to reconstruct or create custombiological pathways. Biological pathways can include a number of genesthat encode peptides or proteins, which play specific signaling,metabolic, structural or other biochemical roles in order to carry outvarious molecular pathways.

As used herein, the terms “biochemical activity” and “biochemicalpathway activity” refer to activity of a biochemical pathway. Pathwaysof interest include, without limitation, butyrate production pathways,LPS biosynthesis pathways, methane gas production pathways, sulfide gasproduction pathways, flagellar assembly pathways, ammonia productionpathways, putrescine production pathways, oxalate metabolism pathways,uric acid production pathways, salt stress pathways, biofilm chemotaxisin virulence pathways, TMA production pathways, primary bile acidpathways, secondary bile acid pathways, acetate pathways, propionatepathways, branched chain amino acid pathways, long chain fatty acidmetabolism pathways, long chain carbohydrate metabolic pathways,cadaverine production pathways, tryptophan pathways, starch metabolismpathways, fucose metabolism pathways.

B) Taxa Groups

In certain embodiments, functional activities include the activities ofone or more taxa groups. Microbial taxa include taxonomic designation atany taxonomic level, e.g., species, genus, order or phylum. Activemicrobial taxa are taxa that are not really present but that aremetabolically active, e.g., as measured by transcriptional levels of themicrobial genome. Groups of microbial taxa whose activity contribute tofunctional activity in a functional category are referred to herein as“taxa groups”. So, for example, pro-inflammatory taxa group can compriseone or more of: proteobacteria, opportunistic bacteria or pathogens,viruses; anti-inflammatory taxa group can comprise one or more of:butyrate producers, Lactobacilli and Bifidobacteria; intestinal barrierdisruptors taxa comprise one or more of: Ruminococcos torques,Ruminococcus gnavus, Serratia, Sutterella, and other mucus-degrading orepithelial layer-disrupting organisms.

Taxa groups of interest include, without limitation, Prevotella(genus)/Bacteroides (genus) ratio, Eubacterium rectale (species),Eubacterium eligens (species), Faecalibacterium prausnitzii (species),Akkermansia muciniphila (species), metabolic-related probiotic species(functional group), Roseburia (genus), Bifidobacterium (genus),Lactobacillus (genus), Clostridium butyricum (species), Allobaculum(genus), Firmicutes (phylum)/Bacteroidetes (phylum) ratio,Lachnospiraceae (family), Enterobacteriaceae (family), Ralstoniapickettii (species), Bilophila wadsworthia (species).

2. Integrative Functional Activities

Examples of integrative functional categories include, withoutlimitation, inflammatory activity, metabolic fitness, digestiveefficiency, intestinal barrier health, protein fermentation, gasproduction, microbial richness, SIBO-like Pattern, detoxificationpotential (ability of microbiome to detoxify the body), gutneuro-balance (impact of microbiome on the brain, e.g., by production ofneurotransmitters), neurological health, cardiovascular health, hormonalbalance, musculoskeletal health, hepatic function, urogenital health,mitochondrial activity, immune function, gastrointestinal health,diabetes, skin conditions and infectious disease.

3. Hierarchical Functional Activities

Functional categories can be hierarchical in nature, with functionalcategories at lower levels in the hierarchy being aggregated intofunctional categories at higher levels in the hierarchy. For example, ata lowest level a single biochemical pathway or a group of microbial taxacan serve as a function category. Combinations of pathways and microbialtaxa groups can be integrated into higher level categories. Thisincludes, for example, a plurality of pathways, a plurality of taxagroups or at least one pathway and at least one taxa group. Referring toFIG. 3, inflammatory activity is a functional category that aggregatedpro-inflammatory and anti-inflammatory components. Each of thesecomponents represents a functional category. In turn, each of thepro-inflammatory and anti-inflammatory categories aggregated scores frombiochemical pathways and taxa groups. Referring to FIG. 4, a number offunctional categories can be aggregated into a higher order functionalcategory, in this case, digestive efficiency. More specifically, in thisexample, digestive efficiency aggregated scores from the categoriesprotein fermentation, motility/gases, intestinal barrier health andSIBO-like/hypochlorhydrea pattern. While the final aggregated functionalcategory is provided with a functional activity score, each subfunctional category which is comprised within the highest functionalcategory may itself be provided with a discrete score or other logic maybe used to aggregate functional activities of the subcategories into thetopmost functional category.

4. Functional Activity Score

A “functional activity score” refers to a quantitative measure assignedto an activity or state of a functional activity. A functional activityscore can be assigned to a functional category in a subject based on-omic data, e.g., data from the microbiome, such as meta-transcriptomicdata. A functional activity score can be determined, for example, basedentirely on the score for a pathway functional activity. Alternatively,where the functional activity is a composite of more than one pathwayand taxa activity scores, optimality can be determined by reference toscores in a population of individuals.

A functional activity score can be given as within or outside areference value, such as a range. The reference value can be derivedfrom values across a population of subjects. For example, the referencerange may constitute a statistical range within the population, such asa standard deviation from the mean. Alternatively, the reference rangemay be determined by expert analysis, by logic and/or with reference toliterature sources. The value can be given as a continuous or discretevariable. For example, discrete variables can be given as “low” “medium”or “high”, with “medium” constituting the reference range. Both “low”and “high” may be outside the reference range. Alternatively, the scorecan be given as “good”, “average” or “needs improvement”. A score of“needs improvement” indicates a score outside of a reference range forwhich action is recommended.

A functional activity score outside of a reference range can beconsidered suboptimal and indicative of the presence of a functionalactivity condition.

Quantitative measures can be given as a discrete or continuous range.Quantitative measures can be absolute numbers or relative amounts, suchas normalized amounts. Quantitative measures include statisticalmeasures such as mean, variance and standard deviation. For example, aquantitative measure can be a number, a degree, a level or bucket. Anumber can be a number on a scale, for example 1-10. Alternatively, thequantitative measure can embrace a range. For example, ranges can behigh, medium and low; severe, moderate and mild; or actionable andnon-actionable. Buckets can comprise discrete numerals, such as 1-3, 4-6and 7-10. quantitative measure (number, range, relative amount, etc.).

IV. Food Information

A. Knowledge Database

A knowledge database is provided from which personalized recommendationscan be made. The database includes, for each of a plurality of fooditems, e.g., foods, supplements and/or ingredients, an entry indicatinga desirability rating of the food for particular biological conditions.The desirability rating can indicate the effect, e.g., the relativedegree of harm or benefit, that consuming the food has on the biologicalcondition. The form of the entries can be hierarchical in nature, frommost beneficial to least beneficial for the condition. The entries canbe in the form of recommendations on whether the food of supplementshould be consumed to ameliorate the condition. There typically will bea plurality of recommendation categories, for example, at least orexactly any of 2, 3, 4, 5, 6 or 7. For example, the categories can be,from most to least beneficial, “good”, “neutral” or “bad”.Alternatively, the categories can be “superfood”, “enjoy”, “minimize”and “avoid.” Alternatively, the categories can be ranked “1”, “2”, “3”,“4” or “5” to designate least to most beneficial for a particularcondition. An exemplary food recommendation database is presented inFIG. 2. Each entry (row) represents a food or micronutrient. Each column(feature) represents a biological condition (phenotype conditions andfunctional activity conditions). Each cell indicates the classificationof the food or nutrient for the particular biological condition. In thiscase, foods and nutrients are classified hierarchically from mostbeneficial to least beneficial as one of four recommendations for thecondition: “superfood”, “enjoy”, “minimize” and “avoid.”

Foods, supplements or ingredients may be classified simply as positive,e.g., “recommended” or neutral, e.g., no recommendation given. Incertain embodiments, supplements are given a positive, neutral ornegative desirability rating, a positive or negative rating or apositive or neutral rating. Ingredients can be given ratings from thesame hierarchical structure as foods, e.g., “super ingredient”, “enjoy”,“minimize” and “avoid”.

Particular recommendations can be assigned by experts based on knowledgefrom literature about the effect of a food on a condition and on expertknowledge. Published literature in peer reviewed journals can bereviewed, prioritizing human studies with large cohorts and havingsufficient confidence intervals, or having placebo groups. These typesof studies can be supplemented with smaller studies with less wellderived effects, or with conditions having fewer journal articlescovering the association.

B. Foods, Supplements and Ingredients

The methods and compositions described herein can be used to providefood, supplement and/or ingredient recommendations to an individual. Therecommendations are based on the predicted effects of the food,supplement and/or ingredient on one or more biological conditions of theindividual.

To provide the recommendations, the effects of a food, supplement and/oringredient on a plurality of conditions, e.g., at least 1, 2, 3, 4, 5,6, 7, 8, 9, or 10 biological conditions of the individual, may bepredicted and the predicted effects may be combined to produce anoverall recommendation for the food, supplement or ingredient. Thepredicted effect corresponds to the desirability, e.g., the desirabilityof a food, which in turn corresponds to the recommendation for the food.For example, a food with a negative effect on a biological condition isa highly undesirable food, and a recommendation for that food could be“avoid” or “minimize,” depending on the degree of the negative effect.The process may be repeated for a desired number of foods and/orsupplements. The recommendations may be in the form of an indication ofthe desirability of intake of the food, supplement and/or ingredient.Any suitable number of levels of desirability may be designated for afood, e.g., at least 2, 3, 4, 5, or 6 levels of desirability. Forexample, in the case of a food, four levels of desirability may be used,such as emphasize the food in the diet (e.g., a “superfood,”), food canbe eaten regularly, such as once every one or two days (e.g., “enjoy”),the food can be eaten sometimes, such as once a week (e.g., “minimize”),or don't allow the food in the diet (e.g., “avoid”). This division oflevels of desirability is exemplary and any suitable number of levelsmay be used. For a supplement, type of supplement, which may includespecific brand of supplement, and, optionally, dosing and/or timing ofthe supplement may be supplied.

Any desired number of foods and/or supplements may be included in therecommendations. In some cases, at least 5, 10, 15, 20, 30, 40, 50, 60,70, 80, 90, 100, 120, 150, 200, 250, or 300 foods may be included in therecommendations, with each food having a designation of desirability forthe individual, such as four levels as described above. TABLE 2 providesan exemplary listing of foods for which a designation of desirabilitymay be given.

TABLE 2 Exemplary Foods Abalone Acacia Gum Adzuki Beans Agar Agar AgaveNectar Alfalfa Sprouts Allspice Almond Milk (unsweetened) AlmondsAmaranth Anchovy Apple (medium, organic) Apricot Artichoke ArugulaAsparagus Aspartame Avocado Avocado Oil Bamboo Shoots Banana (small)Barley Basil Bay Leaf Beans (baked or refried) Bean Sprouts Beef (fatty,grass-fed) Beef (lean, grass-fed) Beer Beet Beet Greens Beet Sugar BellPepper (organic) Black Beans Blackberry Black Eyed Peas Black PepperBlack Tea (brewed) Blueberry Bok Choy Bone Broth (fish) Bone Broth(mammal) Bone Broth (poultry) Boston Beans Boysenberry Brazil NutsBreadfruit Broccoli Brown Mushrooms Brown Rice Brown Sugar BrusselsSprouts Buckwheat Buffalo Bulgur Burdock Root Butter Cabbage Cane SugarCanned Vegetables Canola Oil Capers Caraway Seed Cardamom Cardoon(thistle stem) Carob Carrot Cashews Cassava Catfish Cauliflower Caviaror Roe Cayenne Pepper Celeriac Celery (organic) Celery Seed ChanterelleMushrooms Chard Cheese Cherry (organic) Chervil Chestnuts Chia SeedsChicken (dark) Chicken (white) Chickpeas Chicory (root) Chili PowderChlorella Cilantro Cinnamon Cloves Cocoa (unsweetened) Coconut MCT OilCoconut Meat Coconut Milk (unsweetened) Coconut Oil Coconut Water Cod,Alaskan Coffee (brewed, organic) Collard Greens Coriander Cornish GameHen Corn Syrup Corn Tortilla (organic, non-GMO) Couscous CranberryCrayfish Cucumber Cumin Cured Meat Currant Curry Powder Daikon DandelionGreens Dates Dextrose Dill (fresh) Duck Dungeness Crab, Pacific Eel Egg(large) Eggplant Egg White Egg Yolk Elderberry Emu Endive EnokiMushrooms Escarole Farro Fava Beans Fennel Bulb Fennel Seed FenugreekSeed Fermented Vegetables Fiddlehead Ferns Fig Filberts Filberts orHazelnuts Flax Oil Flax Seeds Flounder Freekeh French Fries Fruit JuicesGame Meat (venison, elk) Garlic Ghee Ginger Goat Goat Cheese Goat MilkGoji Berry Goose Gooseberry Gourd Granola Bars Grapefruit Grape LeavesGrape Seed Oil Grapes (organic) Green Beans Green Tea (brewed) GuavaHaddock Halibut, Pacific Hard Squash Heavy Cream (33% fat) Hemp HeartsHerbal Tea (brewed) Herring Hickory Nuts Honey Horseradish Hot Pepper(organic) Huckleberry Hydrogenated Vegetable Oil Iodized Salt JackfruitJerusalem Artichoke Jicama Kale Kamut Kasha Kefir Kimchi Kiwi KohlrabiKombucha Kumquat Lamb Lard Leek Lemon Lentils Lettuce Lima Beans LimeLobster Loganberries Lo Han Lotus Seeds Lychee Maca Macadamia Nuts MaceMackerel Maitake Mushrooms Maltose Mango Mangosteen Manuka Honey MapleSyrup Margarine Marionberry Marjoram Melon Millet Miso Molasses MorelMushrooms Mulberries Mushrooms Mussel Mustard Greens Mustard Seed NattoNectarine (organic) Nutmeg Oatmeal (flavored) Oats Octopus Okra OliveOil Olives Onion Orange Oregano Ostrich Oyster Mushrooms Papaya PaprikaParsley Parsnip Passionfruit Peach Peanuts Pear (organic) Peas PecansPeppermint (fresh) Perch Persimmon Pheasant Pickle (unsweetened)Pineapple Pine Nuts Pinto Beans Pistachios Plantain Plum PomegranatePoppy Seed Pork (lean) Portabella Mushrooms Potato (small, organic)Processed Cheese Processed Meat Prunes Pummelo Pumpkin Pumpkin SeedsQuail Quinoa Radicchio Radish Rainbow Trout Raisins Raspberry Red BeansRed/Green/Romaine Lettuce Rhubarb Rice Cakes (flavored) Rice Milk RiceNoodles Ricotta or Cottage Cheese (2% fat) Rosemary (fresh) Rutabaga Rye(sprouted bread) Saccharin Safflower Oil Saffron Sage SalmonberrySalmon, Pacific (wild-caught) Sardine Sauerkraut Savoury Scallops ScrodSea Salt or Himalayan Salt Seaweed (fresh) Sesame Seeds Sheep CheeseSheep Milk Shellfish Clam Shellfish Oyster Shitake Mushrooms ShorteningShrimp (domestic) Snap Peas Soda (regular or diet) Sole Sour CherriesSour Cream Soybeans (non-GMO) Soy Milk (unsweetened) Spearmint (fresh)Spinach (organic) Spirulina Sprouted Radish Seeds Squid Star FruitStevia Strawberry (organic) Straw Mushrooms Sucralose Sugar (white)Summer Squash Sunflower Seeds Sweet Potato/Yam Swiss Chard Tapioca TaroTarragon Tempeh Thyme Tilapia Tofu Tomato (organic) Triticale Tuna (polecaught) Turbot Turkey (dark) Turkey (white) Turmeric Turnip VanillaExtract Veal Vinegar Vinegar Apple Cider Walnuts Water ChestnutsWatercress Wheatgrass Wheat (sprouted bread) Whey White Beans WhiteFlour White Rice White Tea (brewed) Whole Milk Wild Rice Wine XanthanGum Xylitol Yam or Sweet Potato Yeast Yogurt (flavored) Yogurt (plain)Zucchini Squash

Alternatively, or additionally, one or more supplements may berecommended for the individual. In the case of supplements, at least 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20supplements may be recommended. For supplement recommendations,microbiome features are considered, and the presence or absence ofcertain microbes, and in some cases relative abundances or othermicrobiome information, is used to determine supplement recommendations.TABLE 3 provides an exemplary listing of supplements, some or all ofwhich may be recommended.

TABLE 3 Exemplary Supplements Supplement Category ABx Support ProbioticsAtrantil Digestive Support Berberine Polyphenols BioPro ProbioticsCai-Mag Butyrate Gut Support Digestive Enzymes Ultra Digestive Enzymewith Betaine HCl Formula 20 Digestive Enzyme Gastrus Probiotics GIRevive Digestive Support Glutathione-SR Antioxidant Iberogast ProkineticKlean Probiotic Probiotics Lactoprime Plus Probiotics Meriva 500-SFPolyphenols Ortho Biotic Probiotics PaleoFiber Prebiotic Panplex 2 PhaseDigestive Enzyme PhytoGanix Polyphenols Polyresveratrol SR PolyphenolsPomegranate Plus Polyphenols Prebiotic Powder Prebiotic Pro 15Probiotics Resveratrol Supreme Polyphenols Spectra Reds PolyphenolsTheracurmin HP Polyphenols Theraflavone Polyphenols Therbiotic CompleteProbiotics Therbiotic Factor 6 Probiotics Ultraflora Spectrum ProbioticsVital 10 Probiotics VSL 3 Pouch Probiotics

Ingredients are components of food or supplements. They include, forexample:

-   -   Probiotics (each subject can get specific strains or species        recommended, and some subjects may not get a probiotic        recommendation): B. Infantis, S. thermophilus, Lactobacillus        curvatus, L. paracasei, L. plantarum, L. delbrueckii subsp.        Bulgaricus, Lactobacillus gasseri, L. amylovorus (LA), L.        fermentum, Lactobacillus rhamnosus;    -   Prebiotics (each subject can get specific types of        oligosaccharides, and some subjects may not get a prebiotic        recommendation at all): FOS, Inulin, Resistant Starch, Arabinan,        PHGG;    -   Foods/herbs/seeds and or some of their extracts: African Mango,        Aloe Vera Leaf Gel, American Ginseng, Berberine, Gymnemma        Sylvestre, Fenugreek, Milk Thistle, Bittermelon, White Kidney        Bean extract;    -   Vitamins/Minerals: Vitamin C, B-vitamins (various), Vitamin A,        Calcium, Selenium;    -   Various nutrients: Alpha-Lipoic-Acid, Anthocyanins (can vary),        Curcumin, Butyrate, Glutamine.

C. Predicted Glycemic Response

The dataset analyzed by the recommendation engine can include an entryfor predicted glycemic response of a subject to. One such method isdescribed in U.S. provisional patent application 62/804,737, filed Feb.12, 2019. In one such method, data are collected from a plurality ofstudy participants, each of whom has consumed one or more foods/mealsover the course of the study. Raw data used to build a training datasetcan include various kinds of -omic data such as gut microbiome genomicor transcriptomic data, blood transcriptomic data and/or urinemetabolism of data. Such data can be abstracted into features thatdescribe types and amounts of microbes in a subject's microbiome as wellas gene expression levels and/or activity of biochemical pathways. Alsoincluded in the dataset are phenotype data about each individualsubject. Such data can be abstracted from responses by subjects toquestionnaires. Meal data for each subject can include data about eachmeal consumed by a subject during the study. Meal data can includemacronutrient and micronutrient information about each meal/food as wellas the time of consumption. The dataset can also include activity/sleepdata indicating amount and/or quality of sleep, timing of sleep, amountand/or intensity of physical activity and its timing. Glycemic responsedata can include raw glycemic response data that provides a quantitativemeasure of blood glucose levels in response to consumption of a meal.Such data can be abstracted to classify the glycemic response.Classifications can be discreet (e.g., high or low, or on a numericscale) or continuous (e.g., on a continuous scale). In some cases, thedimensionality of the data can be reduced to make it more tractable fora learning algorithm. A machine learning algorithm can be trained on thedataset to generate one or more models that predict the glycemicresponse of an individual to a food based on the food's macronutrientprofile, the subject's phenotypic data and omic data from the subject. Amacronutrient profile can include absolute or relative amounts of eachof a plurality of macronutrients in a food or meal, on, for example, amass or calorie basis.

In the dataset, predicted glycemic response can be assigned a positiveor negative desirability rating, e.g., “enjoy” or “minimize”. Thisrating can be used as another food ratings, e.g., a rating of “minimize”is prioritized over “enjoy” or “superfood”.

D. Food Sensitivity Information

In certain embodiments, information regarding sensitivity to aparticular food antigen or antigens may also be used in the systems andmethods presented herein. Without being bound by theory, it is thoughtthat, for a given individual, certain foods or food antigens may causesensitivity in the individual to that food or food antigen, e.g.,mediated by IgG binding. Thus, in certain embodiments, information foran individual may include information regarding food sensitivities ofthe individual. This may involve testing at least 1, 2, 5, 10, 15, 20,30, 40, 50, 70, 100 or more than 100 food antigens for reaction with asample from the individual, such as blood, urine, hair, skin, or anysuitable sample, e.g., a blood sample or sample derived from a bloodsample such as serum or plasma. Any suitable method of determiningsensitivity may be used, for example, an ELISA test or microbead-basedassay, where a surface is coated with a ground-up food (food antigen)and IgGs from serum/plasma are allowed to bind to the antigens, and thepresence of bound IgGs is detected.

In the dataset, food sensitivities can be assigned a negativedesirability rating, e.g., “high sensitivity”. A rating of highsensitivity can take priority over other desirability ratings, producinga final recommendation of “avoid”.

V. Personalized Food Recommendations

To determine a predicted effect of a food on an individual, whichcorresponds to its desirability, and, in turn, the recommendation forthat food, its predicted effect on some or all of the biologicalconditions of the individual may be assessed. It will be appreciatedthat the same food may be beneficial for some biological conditions anddetrimental for others, all of which may be present in the sameindividual. The predicted effects of the food on the biologicalconditions of interest may be combined to give an overall predictedeffect, or desirability, and in turn a recommendation, for the food forthe individual. The process of combining the predictedeffects/desirability/recommendation may be any suitable process. Incertain embodiments, the most negative effect, e.g., the effect thatleads to the least desirability and lowest recommendation among theeffects/desirability/recommendations predicted for the biologicalconditions considered, is chosen. However, other processes may be usedfor combining different effects/desirability/recommendations for thesame food for different biological conditions in an individual. Forexample, the effects/desirability/recommendations for some conditionsmay be weighted more heavily than others. As an example, in the case ofa food that is highly effective at improving cardiovascular condition,and thus would have a “superfood” designation for cardiovascularcondition, but that also causes an increase in acne, and thus would havea “minimize” or “avoid” designation for acne, the effect oncardiovascular condition could be weighted, e.g., 10-fold more heavilythan the effect on acne, and the combined designation would still be“superfood.” This is merely exemplary and any suitable method ofweighting effects/desirability/recommendations for different biologicalconditions may be used, or any other suitable method for combiningeffects/desirability/recommendations when they are different fordifferent biological conditions in an individual.

Typically, a recommendation engine will execute logic by computer tocombine desirability ratings of a food, supplement or ingredient to makea final desirability recommendation. Exemplary rules for such a logicare described herein.

In addition, the database can indicate, for each food or supplement inthe database, a predicted glycemic response to the food or supplement.

In addition, the database can indicate, for each food or supplement,whether the subject has an adverse sensitivity to the food orsupplement.

An automated program may be used to keep track of assessments for agiven food and, when a final rating for that food is reached, place therating on a list of foods that includes the given food, and, optionally,translate the bases of the rating to text that gives an explanation tothe user of the food 1 is as to why the given food was assessed with itsrating. Generally, the text will be at a level that can be understood bya layman without expertise in the technical knowledge used in thealgorithm. Thus, at the end of the process, a list of foods may begenerated where the list includes foods, a recommendation for at leastsome of the foods, e.g., for each food on the list (e.g., “superfood,”“enjoy,” “minimize,” or “avoid,” or any other suitable system ofrecommendation), and, optionally, for some or all of the foods, anexplanation in language understandable to the layman as to why each foodwas given its particular recommendation. The list of foods may includeat least 2, 5, 10, 25, 50, 75, 100, 150, 200, 250, or 300 differentfoods; in some cases, some or all of the foods are given a rating (e.g.,“superfood (indulge),” “enjoy,” “minimize,” or “avoid,” or any othersuitable system of recommendation), and in some cases, some or all ofthe ratings include an explanation in language understandable to thelaymen as to the reasons for the rating. The explanation may includeinformation as to one or more biological conditions of the individual,and/or one or more effects of one or more biological conditions, and howand why the food was rated as related the biological condition and/oreffects of the condition. In some cases, all ratings may be explained.In some cases, only some ratings may be explained, for example, foodswith the designation “superfood (indulge)” or “avoid” may be explained.The list may be provided in any suitable form, such as one or more of apaper listing, a listing on a website where a user can find theirindividual listing, a listing on an application (“app”), and the like.

To determine the effects/desirability/recommendations for a food for abiological condition, any suitable method may be used. For example, acombination of one or more of the effects/desirability/recommendationsof macronutrients in the food on the condition, theeffects/desirability/recommendations of specific compounds in the foodon the condition, and the effects/desirability/recommendations ofinteraction of the food with the microbiome may be assessed.

A food may be assigned to a food group and the effects of the group maybe assessed. For example, milk can belong to the non-fermented dairyfood group, and yogurt belongs to the fermented dairy group or fermentedfood group. A food may belong to no food group, only one food group, ormore than one food group; in certain embodiments, a food belongs to onlyno food group or one food group; i.e., food groups are non-intersectingsubsets of the entire set of foods examined. In certain embodiments, oneor more food groups may be based on the relevance of the foods in thegroup to certain conditions. For example, a fermentable sugars foodgroup (foods containing significant levels of fermentable sugars) isrelevant to the biological condition of small intestinal bacterialovergrowth (SIBO).

In certain embodiments, the effects/desirability/recommendations ofmacronutrients in the food (or food group to which the food belongs) fora given biological condition are assessed. In some cases, macronutrienteffects/desirability/recommendations are assessed first. Macronutrientsused in this analysis can include any suitable group of macronutrients,such as carbohydrates, fiber (generally indigestible carbohydrates),proteins, and fats. The food (or food group) is given a firstrecommendation based on the likely effect of its macronutrients on thebiological condition. The recommendation may be one of two, three, four,or more than four possible recommendations, for example, therecommendation may be one of three possible recommendations, such as“enjoy,” “minimize,” or “avoid.” For example, if an individual is foundto have the biological condition of dysglycemia (hyperglycemia), thefood beet sugar, whose macronutrient content is entirely simplecarbohydrates, would receive a rating at this step of “avoid.” Thus, incertain cases, the effects of macronutrients in the food or food groupon the biological condition may be so detrimental that the food or foodgroup receives a recommendation of “avoid” based solely on macronutrientcontent, and no further assessment may be performed. If the rating is“minimize” or “enjoy,” further steps may be performed to determine afinal rating.

The effects/desirability/recommendations of specific compounds in thefood on the biological condition can alternatively or additionally beassessed. In certain embodiments, this assessment comes after theassessment for macronutrient effects/desirability/recommendations.Specific compounds in the food can include micronutrients, as well asother relevant compounds that are not micronutrients, such as purines.Exemplary specific compounds whose effects can be assessed in this stepare shown in Table 4. Micronutrients can include, for example, amineral, a trace mineral, a vitamin, a biochemical substrate, or anycombination thereof. A mineral may be calcium, magnesium, sulfur, or anycombination thereof. A trace mineral may be iron, chromium, copper,fluoride, iodine, manganese, molybdenum, selenium, zinc, or anycombination thereof. A vitamin may be thiamin (B1), riboflavin (B2),niacin, Vitamin B6, cobalamin (B12), folate, ascorbic acid, Vitamin A,Vitamin D, Vitamin E, Vitamin K, or any combination thereof. It will beappreciated that a given food or food group may have a large variety ofspecific compounds and one or more of the specific compounds may affecta biological condition; a database of foods, food groups, and conditionsmay be established that indicates theeffects/desirability/recommendations of the typical specific compoundprofile of the food or food group on a particular condition. In certaincases, foods are classified based on the presence of 1, 2, 3, 4, 5, ormore than 5 specific compounds, for example, one specific compound. Inthe latter case, for example, a food may be classed as apurine-containing food based on its typical purine content, regardlessof its content of other specific compounds. The predictedeffects/desirability/recommendations of the food or food group on thebiological condition is assessed based on its specific compound profile,and the recommendation based on macronutrients may remain the same, orit may be upgraded or downgraded. For example, a food or food group canmove from “enjoy” to “superfood,” or from “minimize” to “avoid,” or from“minimize to enjoy,” etc. In certain cases, the rating for a food orfood group can change up to 2 levels (e.g., from “enjoy” to “avoid”), orone level (e.g., a food can change from “minimize” to “enjoy” but notfrom “minimize” to “superfood”), or a combination thereof. In somecases, a food may be downgraded but not upgraded, or only upgraded tothe level of “enjoy.”

TABLE 4 Exemplary Specific Compounds Absorbable Carbohydrate AdenineNutrient Aglycone Allergen Protein Allicin Alliin Allyl Cysteine AlphaLinolenic Acid amino acids Anethole Anthocyanidin Nutrient AnthocyaninApigenin Arginine Ascorbic Acid Avenanthramide Avenanthramide NutrientAvenanthramide B carotene PhenolicAcid B vitamins Beta Carotene BetaGlucan Cereal Biotin Butyrate Butyric Acid Caffeine Caffeine NutrientCalcium Calcium Ion2 Capsaicin Casein1 Casein2 Catechin CholesterolCholine Citrulline Cobalamin CoEnzymeQ10 Collagen Cyanidin CysteineDaidzein Delta-7-sterine Deta-sitosterol DodecanoicAcid EGCG(LauricAcid) EicosaPentanoicOmega3 ELLAGIC EllagicAcid EpicatechinEpigallocatechin Gallate Essential fatty acids Fatty Acid Fatty Acidferulic acid Nutrient Omega3 Nutrient Omega9 fiber FlavonoidNutrientfolate folic acid FOS FructOligoSaccharide FructoseGalactOligoSaccharide GamaAminoButyricAcid GammaAminoButyricAcidGammaLinolenicAcid gingerol GingerolNutrient GLA GlucobrassicinGlucoraphanin GlucosinolateNutrient glucosinolates Glutamine GLUTENGlycemicIndex GlycemicIndex/Glycemic glycoside Load GuanineNutrientHypoxanthineNutrient Inulin iodine IodineNutrient iridoid glycoside ironIronIon2 kampferol Lactalbumin Alpha Lactalbumin Beta Lactose lauricacid Lectin Lignan Nutrient Limonin Glucoside Linalool Linoleic AcidLutein Lutein Zeaxanthin Luteolin Lycopene magnesium Magnesium Ion2Maltose Mannitol medium chain triglycerides Medium Chain Fatty AcidMucilage MUCIN Nutrient MUFAs Naringenin niacin Nitrate NitriteOleicAcid OXALATE pantothenic acid phospholipids phosphorusPhytonutrient Nutrient phytonutrients Phytosterol Nutrient phytosterolsPolyphenol Nutrient polyphenols PolysaccharideInsoluble PolysaccharideInsoluble Fiber Nutrient Nutrient Polysaccharide Soluble PolysaccharideSoluble potassium Fiber Nutrient Nutrient Potassium Ion Potassium Ion1probiotics protein pyridoxine Quercetin Resistant Starch Nutrientresveratrol Retinoid Nutrient riboflavin S Adenosyl Methionine SaponinGlycoside Saponin Phytonutrient saponins Saturated Triacylglycerol Fatselenium Selenium Nutrient Sesquiterpene Lactone Sinigrin sodiumSodiumIon1 Sorbitol Tannoid Nutrient Theanine Theobromine NutrientTheophylline Nutrient thiamin thiamine thiols Total Anthocyanidin TotalCarbohydrate By Total Copper Total Fiber Carbohydrate DifferenceNutrientNutrient Total Total Total Goitrogen FructoOligosaccharideGalactoOligosaccharide Total Inulin Total Iron Total Oxalate TotalPhosphorous Total Polyphenol Total Protein Total Purine Total SulfurTryptophan VitAIU Vitamin C Vitamin E Vitamin A Vitamin B12 Vitamin B6Vitamin C Vitamin D Vitamin E Vitamin K VIT B VITB2_Total RiboflavinVITB3_Total Niacin VITB5_Total VITB6_Total PLP PantothenicAcid VITB9VITB9_Total Folate VITE VITK_TotalMK XanthineNutrient Zeaxanthin ZincZinc Ion2

The effects/desirability/recommendations of the food in relation to themicrobiome can alternatively or additionally be assessed. In certainembodiments, combined effects of foods or food groups and microbiome onbiological conditions are assessed. In other embodiments, foods areassessed without reference to biological conditions; e.g., a food orfood group that has already been assigned a rating for an individual,such as by assessment of macronutrients and/or specific compounds, isassessed to see if microbiome effects will alter the rating. In somecases, the rating can remain the same, be upgraded, or be downgraded,depending on the individual's microbiome. In some cases, the rating canremain the same or be downgraded depending on the individual'smicrobiome. Any suitable method of determining a microbiome effect for agiven individual may be used. In certain cases, microorganisms (usedherein to include viruses) are assessed at any suitable level, such asat the genus, species, or strain level. In certain cases, microorganismsassessed include one or more of bacteria, fungi, archaebacteria,viruses, protists, or any combination thereof. In certain cases,bacteria and viruses are assessed. In certain cases, bacteria, viruses,and fungi are assessed. In certain cases, bacteria, viruses, andarchaebacteria are assessed. In certain cases, bacteria, fungi, viruses,and archaebacteria are assessed. One or more microorganisms may beassessed, e.g., at least 1, 2, 3, 4, 5, 6, 7, or 8 microorganisms. Themicroorganism or microorganisms may be assessed at the genus, species,or strain level, or any combination thereof. The assessment can be anysuitable assessment. For example, the assessment may be based partiallyor entirely on the presence or absence of one or more microorganisms,for example, at the genus or species level. The assessment can befurther refined in terms of quantity or relative quantity of themicroorganism or microorganisms, and if more than one microorganism isassessed, the different microorganisms may be weighted or otherwisemanipulated in producing a final recommendation. In certain embodiments,the assessment of the microbiome is used at least in part to determinewhether a particular food or food group or components thereof will bealtered by the microorganism or microorganisms, in such a way as to bebeneficial or detrimental. For example, if the food spinach is rated as“enjoy” after an initial assessment, such as assessment ofmacronutrients and specific compounds, the presence or absence of thegenus Oxalobacter and/or species Oxalobacter formigenes, which acts onthe oxalate in spinach, may be assessed. If the genus/species ispresent, then spinach remains at “enjoy,” but if absent, spinach isdowngraded to “minimize.” Thus, in this case, the absence (or lowlevels) of a microorganism causes the food rating to be downgraded.Another example is if the microbiome contains pepper mild mottle virus,the recommendation for bell peppers may be downgraded. In this case, thepresence (or high levels) of a microorganism may cause the food ratingto be downgraded.

The effects of a food or food group on food sensitivities in theindividual may additionally or alternatively be assessed, and used todetermine and/or modify food recommendations for the individual asappropriate. In certain cases, one or more food sensitivities for theindividual may be used to modify food recommendations. In certain cases,although food recommendations are not modified based on one or more foodsensitivities, the individual is informed of the one or more foodsensitivities; for example, the individual may be informed of theirlevel of sensitivity to a food, which can be one of at least 1, 2, 3, 4,or more than 4 levels; e.g., levels of sensitivity can be designated as“none,” “low,” “medium,” or “high,” and the individual informed of thedesignation; additionally, the individual may be informed that a foodcontains antigens from relevant foods (e.g., kefir contains yeast, milk,whey, and casein). A combination of the two approaches may be used. Incertain embodiments, after a food or food group has been given adesignation based on, e.g., macronutrient, specific compounds, and/ormicrobiome, food sensitivity information is used to modifyrecommendations as needed; in certain cases, food sensitivity for aparticular food may be ranked in terms of severity and that informationcan inform whether or not, and/or to what degree, to modify foodrecommendations. Food sensitivity test results can be used to move afood from a higher consumption recommendation to a lower one, due to apositive test for the specific food; for example, a food can be movedfrom the “enjoy” to “minimize” or “avoid” category if it is found thatthe individual is sensitive to that food; the decision to alter therecommendation, and/or the degree to which the recommendation isaltered, may be determined by any suitable method, e.g., if anindividual is found to be highly sensitive to a particular food it maybe moved more than one rank in recommendation, such as from “enjoy” to“avoid;” alternatively or in addition, a higher sensitivity to aparticular food may cause a larger set of foods to be downgraded inrecommendation than a lower sensitivity to the food. In certain cases,foods known to cross-react with a particular food to which theindividual is found to be sensitive may also have their recommendationaltered (and/or the individual alerted to the cross-reactivity). Forexample, if a person is found to be sensitive to tuna, therecommendation for cross-reactive food such as salmon may be adjusted,e.g., moved downward, based on the cross-reactivity. In certain cases,multiple foods can belong to a food group whose recommendations may bealtered by the sensitivities of an individual to foods within the group.For example, if an individual tests as sensitive to tomato, pepper, andpotato, which are members of the nightshade family, this could affectadditional nightshade-related recommendations; whether or not, and/or towhat degree, recommendations for foods in a food group are altered basedon food sensitivities to members of the group may depend on how manyfoods in the group the individual is sensitive to and/or the severity ofthe sensitivity. In certain cases, recommendations for foods to whichthe individual is not sensitive may be affected by the food sensitivityinformation. A food to which the individual is not sensitive can bemoved to a higher level of recommendation because it possesses one ormore characteristics that overlap with those of a food to which theindividual is sensitive. This can be based on macronutrient and/orspecific compound (e.g., micronutrient) composition of the respectivefoods. For example, if two foods both contain a necessary micronutrient,they may initially be placed in the “enjoy” category; if an individualis found to be sensitive to one but not the other, the food to which theindividual is sensitive may be downgraded to “minimize” or “avoid,”while the food to which the individual is not sensitive may be upgradedto “indulge” (e.g., superfood).

In certain embodiments, only one of predictedeffects/desirability/recommendations of macronutrient, specificcompound, or microbiome of a particular food or food group is used togenerate a recommendation for a food. In certain embodiments, two ofpredicted effects/desirability/recommendations of macronutrient,specific compound, or microbiome of a particular food or food group isused to generate a recommendation for the food. In certain embodiments,all three of predicted effects/desirability/recommendations ofmacronutrient, specific content, or microbiome of a particular food orfood group is used to generate a recommendation for the food.

As discussed above, when more than one biological condition is present,a given food or food group may generate more than one recommendation,and the recommendations may be combined in any suitable manner, such aschoosing the most restrictive recommendation. Thus, one or more ofassessment for a food of macronutrient, specific compound, and/ormicrobiome effects may be performed for any suitable number ofbiological conditions in an individual, such as 1, 2, 3, 4, 5, or morethan 5 conditions, depending on the number of conditions for theindividual, and the recommendations for the food for the differentconditions can be combined as described herein.

Supplements may be classified as probiotics, digestive support,polyphenols, gut support, digestive enzymes, antioxidants, prokinetic,or prebiotic. See Table 3 for an exemplary list of supplements. Forsupplement recommendations, microbiome features are considered, and thepresence or absence of certain microbes, and in some cases relativeabundances or other microbiome information, is used to determinesupplement recommendations.

In classifying a food based on its desirability for a subject, therecommendations for the food for each biological condition for which thesubject is sub-optimal can be taken into account. Various algorithms canbe used for this purpose. For example, a value of central tendency(e.g., average or variance) of all the recommendations for allsub-optimal biological conditions can be used. For example, if thevalues for four biological conditions, or a scale of 1-4 are 3, 2, 4 and4, the designation could be the average, in this case, 3.25, which mightbe rounded to “3”. Scores can be weighted, that scores for certainconditions count for more than other conditions. For example, a scorefor inflammatory activity might be given twice the weight of a score forgas production.

In one embodiment, the final score is assigned based on a logic thatuses a hierarchical process of elimination. In one such method, it isdetermined whether the food has a least beneficial rank designation forany biological condition present; if so, that rank is assigned as thefood recommendation for the subject. If no biological conditions are soranked, it is determined whether the food has a next higher rankdesignation for any biological condition present; if so, that nexthigher rank is assigned as the food designation. This process continuesfor increasingly beneficial rankings.

In a related embodiment, foods are assigned one of four rankings foreach condition present. These maybe called, from lowest desirability tohighest desirability, for example, “avoid”, “mimimize”, “enjoy” and“superfood”. In addition, the food is assigned to a glycemic responsecategory for the subject, which may qualify as “high” or “low” (orhigh”, “medium” or “low”). In a first pass, it is determined whether thefood is categorized at the least beneficial level (“avoid”) for anycondition. If so, the food is designated “avoid” for the subject. If thefood is not designated “avoid” for any condition, then, in a secondpass, it is determined whether the food is categorized as “minimize”(including a “high” predicted glycemic response) for any condition. Ifso, the food is categorized as “minimize” for the subject. If the foodis not designated “minimize” for any condition, then, in a third pass,it is determined whether the food is categorized as “superfood” for anycondition. If so, the food is categorized as “superfood” for thesubject. If the food is not categorized as “avoid”, “minimize” or“superfood” for any condition present, then the food is designated as“enjoy” for the subject.

FIG. 4 shows an exemplary application of recommendation engine useslogic as described herein to provide final recommendations for a varietyof food items. Knowledge database includes for each of a plurality ofphenotypic conditions and functional activity conditions, a desirabilityrating for each of a plurality of foods, supplements and ingredients.Omic data has been used to infer the presence of biological conditionsin a subject. In this case, phenotype condition to, functional activityconditions one, and functional activity condition n are present.Non-present biological conditions, i.e., phenotype condition 1,phenotype conditions 3, phenotype condition and, functional activitycondition 2, and functionally activity condition 3 are not present inour greyed-out.

Food 1 has a desirability rating of “avoid” for functional activitycondition 1. This rating takes priority over all of the ratings.Therefore, food 1 is given a final recommendation of “avoid”.

Food 2 has no desirability ratings of “avoid” but does have adesirability rating of “minimize” for functional activity condition n.Therefore, it is assigned a final recommendation rating of “minimize”.

Food 3 has no desirability ratings of “avoid” or “minimize”, but doeshave a desirability rating of “superfood” for functional condition 1.Therefore, it is assigned a final recommendation rating of “superfood”.

Food 4 has no desirability ratings of “avoid” “minimize” or “superfood”.Therefore, it is assigned a final recommendation rating of “enjoy”.

Food 5 has a desirability rating of “minimize” for the subject'spredicted glycemic response to the food. Therefore, it is assigned afinal recommendation of “minimize”.

Supplement 1 has a desirability rating of “not recommended” forfunctional activity condition n. Therefore, it is assigned a finalrecommendation of “not recommended”.

Supplement q has a desirability rating of “recommended” for functionalactivity condition 1, but no ratings of “not recommended”. Therefore, itis assigned a final recommendation of “recommended”.

Ingredient 1 has a desirability rating of “avoid” for functionalactivity condition 1. Because the negative desirability rating priorityover other desirability ratings, this ingredient is assigned finalrecommendation of “avoid”.

Ingredient r has a desirability rating of “super ingredient” forphenotype condition 2, but no negative desirability ratings. Therefore,this ingredient is assigned final recommendation of “super ingredient”.

Recommendations for altering diet can be provided to a subject inelectronic or paper format. Electronic communications can becommunicated to the subject over a communications network to anelectronic device accessible by the subject. Data can be transmittedelectronically, e.g., over the Internet. Communication may be, forexample, in the form of information provided on a password-protectedwebsite accessible by the subject. Alternatively, communication may beby email or text message. Electronic devices accessible by the subjectcan include, for example, computers connected to the Internet, smartphones (e.g., iPhone® or Samsung Galaxy®), or a wearable device (e.g.,Fitbit® or Garmin®). Electronic communication can be, for example, overany communications network include, for example, a high-speedtransmission network including, without limitation, Digital SubscriberLine (DSL), Cable Modem, Fiber, Wireless, Satellite and, Broadband overPowerlines (BPL). Information can be transmitted to a modem fortransmission e.g. wireless or wired transmission, to a computer such asa desktop computer. Alternatively, reports can be transmitted to amobile device. Reports may be accessible through a subscription programin which a user accesses a website which displays the report. Reportscan be transmitted to an electronic device accessible by the user. Thiscould be, for example, a personal computer, a laptop, a smart phone or awearable device, e.g. worn on the wrist.

The diet of a subject refers to the total kind and quantities of food,supplements, probiotics, and medicines consumed by a subject over adefined period of time e.g., over the course of about a day, about aweek, about a month or about a year. A diet can be further defined interms of macronutrient and micronutrient content. Macronutrientsinclude, for example, carbohydrates, fiber (generally indigestiblecarbohydrates), proteins, and fats. Macronutrients used in this analysiscan include any suitable group of macronutrients, such as carbohydrates,fiber (generally indigestible carbohydrates), proteins, and fats.Micronutrients include, for example, a mineral, a trace mineral, avitamin, a biochemical substrate, or any combination thereof. A mineralmay be calcium, magnesium, sulfur, or any combination thereof. A tracemineral may be iron, chromium, copper, fluoride, iodine, manganese,molybdenum, selenium, zinc, or any combination thereof. A vitamin may bethiamin (B1), riboflavin (B2), niacin, Vitamin B6, cobalamin (B12),folate, ascorbic acid, Vitamin A, Vitamin D, Vitamin E, Vitamin K, orany combination thereof.

Altering the diet of the subject can alter activity in any number offunctional categories, resulting in desired changes in either specificmicrobial pathways and/or broader biological functions of the microbiomeor of the host (based on the microbiome). In general, an aim of alteringdiet is to rebalance the microbiome of a subject such that functionalactivity scores shift toward or into the reference range. This can beaccomplished by several means. One method is to provide dietary itemsthat promote the production of useful nutrients by the gut microbes.Another method is to reduce or avoid foods high in nutrients that areused by the microbes to produce harmful products. Another method is toprovide a food or supplement containing probiotic microbes that producebeneficial nutrients or “overpower” the harmful microbes or the activitylevels of microbial pathways that yield harmful products. Another methodis to provide the beneficial macro- and/or micronutrients directly inthe available forms of diet and supplement recommendations.

VI. Food and Supplement Delivery

In another aspect, after determining that a functional activity score ofa subject is outside reference range, one or more of a food, asupplement, a probiotic or a medicine can be identified which, whenincluded in the diet of the subject, shifts the functional activityscore toward or into the reference range. So, for example, if it isdetermined that a subject has an inflammatory activity score that ishigh compared with the reference range, dietary items that will decreasethe inflammatory activity score can be identified. These might include,for example, foods or supplements high in antioxidants or probioticsincluding microbes that depress pro-inflammatory biochemical pathways,such as the butyrate pathway.

These dietary items can be delivered to a subject, for example, viacommon carrier. Such items can be provided in a kit, which typicallyincludes a collection of items intended for use together. Kits caninclude containers to hold dietary items. Containers, themselves, can beplaced into a shipping container, such as a box or a bag. The containercan be transmitted by hand delivery or by a common carrier, such as anational postal system or a delivery service such as UPS or FedEx. Kitscan also typically include written recommendations or instructions foruse.

VII. Exemplary Embodiments

1. A method of determining recommendations of desirability of aplurality of different foods for an individual, wherein the individualhas an individual set of biological conditions comprising at least 1biological condition, and wherein the recommendation for each food isbased on its predicted effect on the at least 1 biological condition. 2.The method of embodiment 1 wherein the individual set of biologicalconditions comprises at least 2 biological conditions, and wherein therecommendation for each food is based on combining recommendations forthe food for each of the two conditions. 3. The method of embodiment 1wherein the individual set of biological conditions comprises at least 3biological conditions, and wherein the recommendation for each food isbased on combining recommendations for the food for each of the 3conditions. 4. The method of embodiment 1 wherein the individual set ofbiological conditions comprises at least 4 biological conditions, andwherein the recommendation for each food is based on combiningrecommendations for the food for each of the 4 conditions. 5. The methodof embodiment 1 wherein the individual set of biological conditionscomprises at least 5 biological conditions, and wherein therecommendation for each food is based on combining recommendations forthe food for each of the 5 conditions. 6. The method of embodiment 1wherein the condition is determined from an overall set of biologicalconditions. 7. The method of embodiment 1 wherein the plurality ofdifferent foods comprises at least 2, 5, 10, 20, 30, 40, 50, 70, 100,120, 150, 170, 200, 250, or 300 different foods. 8. The method ofembodiment 1 wherein the recommendation of desirability of the pluralityof different food comprises at least 2, 3, or 4 discrete values ofdesirability, wherein the values are in order of decreasingdesirability. 9. The method of embodiment 1 wherein, if a recommendationof desirability of a food for any of the at least 2 biologicalconditions is different from the others, a final recommendation isdetermined by choosing the most restrictive recommendation. 10. Themethod of embodiment 1 wherein the individual set of biologicalconditions comprises at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 biologicalconditions, and wherein the recommendation for each food is based on itspredicted effect on at least some of the biological conditions in theindividual set of biological conditions. 11. The method of embodiment 10wherein the recommendation for each food is based on its predictedeffect on at least ¼, ½, or ¾ of the biological conditions in theindividual set of biological conditions. 12. The method of embodiment 1wherein the individual is determined to have an individual set ofbiological conditions based on phenotype and microbiome information forthe individual. 13. The method of embodiment 12 wherein the phenotypeinformation is obtained in a process comprising determining response forthe individual to a questionnaire. 14. The method of embodiment 12wherein the microbiome information is obtained from a sample from theindividual. 15. The method of embodiment 14 wherein the sample is astool sample. 16. The method of embodiment 12 wherein the microbiomeinformation comprises transcriptome information. 17. The method ofembodiment 12 wherein the microbiome information comprises informationregarding viruses in the microbiome. 18. The method of embodiment 1wherein determining a recommendation for desirability of consumption ofa first food of the plurality of foods for the individual comprisesperforming at least one of (i) predicting an effect of macronutrientcontent of the first food on a first biological condition in theindividual and determining a first recommendation based on the predictedeffect of macronutrient content of the food; (ii) predicting an effectof one or more specific compounds in the first food on the firstbiological condition in the individual and determining a secondrecommendation based on the predicted effect of the one or more specificcompounds; and (iii) predicting an effect of the first food on amicrobiome of the individual, and determining a third recommendationbased on the predicted effect on the microbiome. 19. The method ofembodiment 18 comprising performing at least two of steps (i)-(iii). 20.The method of embodiment 18 comprising performing all of steps(i)-(iii). 21. The method of embodiment 20 wherein steps (i), (ii), and(iii) are performed in sequential order. 22. The method of embodiment 21wherein a food is given a first recommendation after step (i), then step(ii) is performed and the food is given a second recommendation, whereinthe second recommendation can be the same as the first recommendation oran upgrade or downgrade of the first recommendation, then step (iii) isperformed and the food is given a third recommendation, wherein thethird recommendation can be the same as the second recommendation or anupgrade or downgrade of the second recommendation. 23. The method ofembodiment 1 wherein desirability for consumption of a food can have atleast 2, 3, or 4 values. 24. The method of embodiment 23 where thevalues are graded in terms of desirability. 25. The method ofembodiments 18, 19, or 20, further comprising performing one or more ofsteps (i)-(iii) for a second biological condition, where the secondbiological condition is different from the first, and determining arecommendation for desirability of consumption of the food for thesecond biological condition. 26. The method of embodiment 25 wherein atleast one of steps (i)-(iii) is performed for the second biologicalcondition. 27. The method of embodiment 25 wherein at least two of steps(i)-(iii) is performed for the second biological condition. 28. Themethod of embodiment 25 wherein at all three of steps (i)-(iii) isperformed for the second biological condition. 29. The method ofembodiment 28 wherein steps (i)-(iii) are performed sequentially. 30.The method of embodiment 25 further comprising combining therecommendations for desirability of consumption of the food for thefirst biological condition and for the second biological condition todetermine a combined desirability for consumption of the food. 31. Themethod of embodiment 25 wherein the combining comprises determiningwhether one recommendation for desirability is more restrictive than theother, and, if so, determining that the combined desirability forconsumption of the food is the more restrictive desirability. 32. Themethod of embodiment 25 further comprising performing one or more ofsteps (i)-(iii) for a third biological condition, where the thirdbiological condition is different from the first and second biologicalconditions, and determining a recommendation for desirability ofconsumption of the food for the third biological condition. 33. Themethod of embodiment 32 wherein at least one of steps (i)-(iii) isperformed for the third biological condition. 34. The method ofembodiment 32 wherein at least two of steps (i)-(iii) is performed forthe third biological condition. 35. The method of embodiment 32 whereinat all three of steps (i)-(iii) is performed for the third biologicalcondition 36. The method of embodiment 35 wherein steps (i)-(iii) areperformed sequentially. 37. The method of embodiment 32 furthercomprising combining the recommendations for desirability of consumptionof the food for the first, second, and third biological conditions todetermine a combined desirability for consumption of the food. 38. Themethod of embodiment 37 comprising determining which if any, of therecommendations for desirability of consumption of the food is mostrestrictive, and, if so, determining that the combined desirability forconsumption of the food is the most restrictive desirability. 39. Themethod of embodiment 32 further comprising performing steps (i)-(iii)for a fourth biological condition, where the fourth biological conditionis different from the first, second, and third biological conditions,and determining a recommendation for desirability of consumption of thefood for the fourth biological condition. 40. The method of embodiment39 wherein at least one of steps (i)-(iii) is performed for the fourthbiological condition. 41. The method of embodiment 39 wherein at leasttwo of steps (i)-(iii) is performed for the fourth biological condition.42. The method of embodiment 39 wherein all three of steps (i)-(iii) isperformed for the fourth biological condition. 43. The method ofembodiment 42 wherein steps (i)-(iii) are performed sequentially. 44.The method of embodiment 39 further comprising combining therecommendations for desirability of consumption of the food for thefirst, second, third, and fourth biological conditions to determine acombined desirability for consumption of the food. 45. The method ofembodiment 44 comprising determining which if any, of therecommendations for desirability of consumption of the food is mostrestrictive, and, if so, determining that the combined desirability forconsumption of the food is the most restrictive desirability. 46. Themethod of any of embodiments 18 through 45 further comprisingdetermining a recommendation for desirability of consumption of a secondfood from the plurality of foods, wherein the second food is differentfrom the first, comprising performing one or more of steps (i)-(iii) forthe second food, for at least 1, 2, 3, 4, or 5 biological conditionsfrom the individual set of biological conditions. 47. The method of anyof embodiments 18 through 45 wherein one or more of steps (i)-(iii) areperformed for at least 2, 5, 10, 20, 50, 100, 150, 200, 250, or 300different foods. 48. The method of any of embodiments 1 through 47wherein one or more of the foods are classed as part of a food group andthe prediction of one or more of steps (i), (ii) and/or (iii) is basedon the food group. 49. The method of any of the previous embodimentsfurther comprising providing an explanation for the recommendations forat least some of the foods to the individual, wherein the recommendationis determined from results of one or more steps of analysis of the foodand its effect on one or more conditions of the individual. 50. Themethod of embodiment 50 wherein the explanation is provided as textsuitable to layman understanding.

51. A method of determining a set of food recommendations for anindividual comprising (i) determining an individual set of one or morebiological conditions for the individual from an overall set ofbiological conditions by combining phenotype and microbiome informationfor the individual; and (ii) determining the food recommendations forthe individual based on the predicted effects of foods and/or foodgroups on one or more of the conditions for the individual. 52. Themethod of embodiment 51 wherein the microbiome information includestranscriptome information. 53. The method of embodiment 51 or 52 whereinthe microbiome information includes taxa information and gene expressioninformation. 54. The method of embodiment 52 wherein the microbiomeinformation includes one, two, three, four, or all of informationregarding bacteria, viruses, archaebacteria, fungi or protists. 55. Themethod of embodiment 51 wherein the predicted effects comprisemacronutrient effects, specific compound effects, microbiome effects, orany combination thereof 56. The method of embodiment 51 wherein, ifpredicted effects of a food or food group lead to differentrecommendations for a food for different conditions, the mostrestrictive recommendation is chosen as the final recommendation.

57. A method of determining a recommendation for desirability ofconsumption of a first food for an individual comprising performing atleast one of (i) predicting an effect of macronutrient content of thefirst food on a first biological condition in the individual anddetermining a first recommendation based on the predicted effect ofmacronutrient content of the food; (ii) predicting an effect of specificcompound content of the first food on the first biological condition inthe individual and determining a second recommendation based on thepredicted effect, wherein the second recommendation can be the same asor different from the first recommendation, depending on themicronutrient effect; and (iii) predicting an effect of the first foodon a microbiome of the individual, and determining a thirdrecommendation based on the predicted effect, wherein the thirdrecommendation can be the same as or different from the secondrecommendation, depending on the microbiome effect. 58. The method ofembodiment 57 wherein microbiome information includes informationregarding the presence or absence, quantity, or other characteristic ofone, two, three, four, or all of bacteria, viruses, archaebacteria,fungi, or protists that may be affected by the first food. 59. Themethod of embodiment 57 comprising performing at least two of steps(i)-(iii). 60. The method of embodiment 57 comprising performing all ofsteps (i)-(iii). 61. The method of embodiment 57 wherein steps (i),(ii), and (iii) are performed in sequential order. 62. The method ofembodiment 57 wherein desirability for consumption of a food can have atleast 2, 3, or 4 values. 63. The method of embodiment 62 where thevalues are graded in terms of desirability. 64. The method of embodiment57 further comprising performing one, two, or all of steps (i)-(iii) fora second biological condition, where the second biological condition isdifferent from the first, and determining a recommendation fordesirability of consumption of the food for the second biologicalcondition. 65. The method of embodiment 64 further comprising comparingthe recommendation for desirability of consumption of the food for thefirst biological condition and for the second biological condition todetermine which, if either, is more restrictive, and determining a finalrecommendation for desirability of the food that is the more restrictivedesirability. 66. The method of embodiment 64 further comprisingperforming one, two, or all of steps (i)-(iii) for a third biologicalcondition, where the third biological condition is different from thefirst and second biological conditions, and determining a recommendationfor desirability of consumption of the food for the third biologicalcondition. 67. The method of embodiment 66 further comprising comparingthe recommendation for desirability of consumption of the food for thefirst, second, and third biological conditions to determine which, ifany, is most restrictive, and determining a final recommendation fordesirability of the food that is the most restrictive desirability. 68.The method of embodiment 66 further comprising performing one, two, orall of steps (i)-(iii) for a fourth biological condition, where thefourth biological condition is different from the first, second, andthird biological conditions, and determining a recommendation fordesirability of consumption of the food for the fourth biologicalcondition. 69. The method of embodiment 68 further comprising comparingthe recommendation for desirability of consumption of the food for thefirst, second, third, and fourth biological conditions to determinewhich, if any, is most restrictive, and determining a finalrecommendation for desirability of the food that is the most restrictivedesirability. 70. The method of embodiment 68 further comprisingperforming one, two, or all of steps (i)-(iii) for a fifth biologicalcondition, where the fifth biological condition is different from thefirst, second, third, and fourth biological conditions, and determininga recommendation for desirability of consumption of the food for thefifth biological condition. 71. The method of embodiment 70 furthercomprising comparing the recommendation for desirability of consumptionof the food for the first, second, third, fourth, and fifth biologicalconditions to determine which, if any, is most restrictive, anddetermining a final recommendation for desirability of the food that isthe most restrictive desirability. 72. The method of any of embodiments57 through 71 further comprising determining a recommendation fordesirability of consumption of a second food, wherein the second food isdifferent from the first, comprising performing one, two, or all steps(i)-(iii) for the second food, for the first, second, third, fourth, orfifth condition, or any combination thereof . 73. The method of any ofembodiments 57 through 72 wherein one, two, or all of steps (i)-(iii)are performed for at least 2, 5, 10, 20, 50, 100, 150, 200, 250, or 300different foods. 74. The method of any of embodiments 57-73 wherein afood can be classed as part of a food group and the prediction of (i),(ii) and/or (iii) is based on the food group. 75. The method of any ofembodiments 57-74 wherein the method further comprises providing anexplanation for the recommendations for at least some of the foods tothe individual, wherein the recommendation is determined from results ofone or more steps of analysis of the food and its effect on one or moreconditions of the individual. 76. The method of embodiment 75 whereinthe explanation is provided as text suitable to layman understanding.

77. A list of food recommendations for an individual, wherein therecommendations are derived from predicting effects of each food on thelist on one or more biological conditions of the individual, wherein theeffects comprise one, two, or all of effects of macronutrient content ofthe food, effects of specific compound effect of the food, and effectsof the food on the microbiome of the individual in relation to one ormore biological conditions of the individual. 78. The list of embodiment77 further comprising, for at least some of the foods, an explanationfor the recommendation for the food, wherein the recommendationindicates one or more probable effects of macronutrient and/or specificcompound content of the food and/or microbiome interaction with thefood, on one or more of the biological conditions, or the effects of oneor more conditions, in the individual. 79. The list of embodiment 78wherein the explanation is in layman's terms. 80. The list of embodiment77 wherein the list comprises at least 5, 10, 15, 20, 25, 30, 40, 50,70, 100, 150, 200, 250, or 300 different food recommendations. 81. Thelist of embodiment 77 wherein each food on the list is designated avalue according to its desirability for the individual. 82. The methodof embodiment 81 wherein each food can have one of at least 2, 3, or 4values for desirability. 83. The list of embodiment 82 wherein each foodcan have 4 values for desirability. 85. The list of embodiment 77wherein the foods are chosen from the foods in Table 2.

86. A method of improving one or more biological conditions in anindividual comprising (i) supplying the individual with food, supplementand/or ingredient recommendations, wherein the food, supplement and/oringredient recommendations are based predicted effects of one or both ofmacronutrient content, specific compound content of the food orsupplement on one or more biological conditions of the individual and,optionally, effect of the food on a microbiome of the individual; and(ii) altering the individual's food, supplement and/or ingredientconsumption so that it more closely matches the food, supplement and/oringredient recommendations. 87. The method of embodiment 86 wherein theone or more biological conditions of the individual are determined byanalysis of phenotype information and microbiome information from theindividual. 88. The method of embodiment 87 wherein the phenotypeinformation is obtained in a process comprising determining responsesfor the individual to a questionnaire and microbiome information isobtained from a sample from the individual. 89. The method of embodiment88 wherein the sample is a stool sample. 90. The method of embodiment 88wherein the microbiome information comprises transcriptomic information.91. The method of embodiment 88 wherein the microbiome informationcomprises taxonomic information and gene expression information. 92. Themethod of embodiment 88 wherein the food recommendations comprises alist of foods, each of which has a designation indicating desirabilityor undesirability of that food for the individual. 93. The method ofembodiment 92 wherein the designation can have one of at least 2, 3, or4 values. 94. The method of embodiment 86 wherein the food, supplementand/or ingredient recommendations are produced by a process comprising(i) selecting an individual set of biological conditions for theindividual from an overall set of biological conditions based on theindividual's phenotype and microbiome information; (ii) determiningoverall predicted desirability of foods, food groups, and/or supplementson at least part of the individual set of biological conditions for theindividual; and (iii) from the results of (ii) determine the food,supplement and/or ingredient recommendations for the individual. 95. Themethod of any of embodiments 86 to 94 further comprising gatheringinformation from the individual regarding phenotype and microbiome afterthe individual has implemented the recommendations for a period of time.96. The method of embodiment 95 wherein the period of time is one weekto one year. 97. The method of embodiment 95 further comprising alteringthe food, supplement and/or ingredient recommendations for theindividual based on the phenotype and microbiome information gatheredafter the period of time. 98. The method of embodiment 86 wherein themicrobiome information comprises information regarding one or morebiochemical molecules in a sample from the individual. 99. The method ofembodiment 98 wherein the one or more biochemical molecule areinformative one or more biochemical activities. 100. The method ofembodiment 98 wherein the information is obtained by a processcomprising quantifying an enzymatic activity assay, a growth-inhibitionculture, metabolic profiling, or any combination thereof 101. The methodof embodiment 98 wherein the biochemical molecule is a small molecule,and wherein the small molecule comprises a metabolite generated by thebiochemical activity. 102. The method of embodiment 101 wherein thesmall molecule comprises a short-chain fatty acid. 103. The method ofembodiment 102 wherein the short-chain fatty acid comprises butyrate.104. The method of embodiment 102 wherein the small molecule comprisespropionate. 105. The method of embodiment 102 wherein the small moleculecomprises a substrate of the biochemical activity.

As used herein, the following meanings apply unless otherwise specified.The word “may” is used in a permissive sense (i.e., meaning having thepotential to), rather than the mandatory sense (i.e., meaning must). Thewords “include”, “including”, and “includes” and the like meanincluding, but not limited to. The singular forms “a,” “an,” and “the”include plural referents. Thus, for example, reference to “an element”includes a combination of two or more elements, notwithstanding use ofother terms and phrases for one or more elements, such as “one or more.”The phrase “at least one” includes “one”, “one or more”, “one or aplurality” and “a plurality”. The term “or” is, unless indicatedotherwise, non-exclusive, i.e., encompassing both “and” and “or.” Theterm “any of” between a modifier and a sequence means that the modifiermodifies each member of the sequence. So, for example, the phrase “atleast any of 1, 2 or 3” means “at least 1, at least 2 or at least 3”.The term “consisting essentially of” refers to the inclusion of recitedelements and other elements that do not materially affect the basic andnovel characteristics of a claimed combination.

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. It is intended thatthe following claims define the scope of the invention and that methodsand structures within the scope of these claims and their equivalents becovered thereby.

What is claimed is:
 1. A method comprising: (a) generating -omic datafrom a subject; (b) determining, from the -omic data, the presence ofone or more biological conditions in the subject; (c) accessing aknowledge base, wherein the knowledge base indicates, for each of aplurality of items selected from foods, supplements and ingredients, adesirability rating of consuming the item for the one or more biologicalconditions; and (d) for each item, implementing computer logic todetermine a final recommendation for the item, wherein the finalrecommendation is based on the combined desirability ratings for thebiological conditions.
 2. The method of claim 1, wherein the subject isa human.
 3. The method of claim 1, wherein the -omic data is generatedfrom a biological sample from the subject.
 4. The method of claim 1,wherein the biological sample comprises a gut microbiome sample or ablood sample.
 5. The method of claim 1, wherein generating -omic datacomprises performing high-throughput sequencing on nucleic acids from asample from the subject to produce sequence data.
 6. The method of claim1, wherein the functional activity conditions are determined fromfunctional activity scores determined from the -omic data.
 7. The methodof claim 5, wherein the functional activity scores are integrativescores comprising more than one type of input data, e.g., KOidentifiers, taxonomy identifiers or human gene identifiers.
 8. Themethod of claim 5, wherein the functional activity scores arenon-integrative scores comprising only one type of input data.
 9. Themethod of claim 1, wherein the -omic data comprises gut microbiomemetatranscriptomic data.
 10. The method of claim 1, wherein thebiological conditions comprise functional activity conditions.
 11. Themethod of claim 10, wherein the functional activity conditions includeor more of: butyrate production pathways, LPS biosynthesis pathways,methane gas production pathways, sulfide gas production pathways,flagellar assembly pathways, ammonia production pathways, putrescineproduction pathways, oxalate metabolism pathways, uric acid productionpathways, salt stress pathways, biofilm chemotaxis in virulencepathways, TMA production pathways, primary bile acid pathways, secondarybile acid pathways, acetate pathways, propionate pathways, branchedchain amino acid pathways, long chain fatty acid metabolism pathways,long chain carbohydrate metabolic pathways, cadaverine productionpathways, tryptophan pathways, starch metabolism pathways, fucosemetabolism pathways, inflammatory activity, metabolic fitness, digestiveefficiency, intestinal barrier health, protein fermentation, gasproduction, microbial richness, detoxification potential (ability ofmicrobiome to detoxify the body), gut neuro-balance (impact ofmicrobiome on the brain, e.g., by production of neurotransmitters),neurological health, cardiovascular health, hormonal balance,musculoskeletal health, hepatic function, urogenital health,mitochondrial activity, immune function, gastrointestinal health,diabetes, skin conditions, infectious disease, stress response,mitochondrial health, mitochondrial biogenesis, oxidative stress, agingand senescence.
 12. The method of claim 10, wherein the -omic datacomprises metatranscriptomic data, and determining functional activityconditions comprises executing computer logic to determine functionalactivity scores from the metatranscriptomic data.
 13. The method ofclaim 10, wherein determining comprises: (i) executing computer logic todetermine biological pathway scores and taxa activity scores, and (ii)deriving functional activity scores from the biological pathway scoresand taxa activity scores.
 14. The method of claim 12, whereindetermining biological pathway scores comprises determining activity offunctional orthologs (e.g., in a KEGG Orthology).
 15. The method ofclaim 12, wherein functional activity scores are measured as continuousvariables or in categories.
 16. The method of claim 15, wherein afunctional activity score outside of a reference range or outside one ormore reference categories indicates a functional activity condition. 17.The method of claim 1, wherein the -omic data comprises phenotypic dataused to determine phenotypic conditions.
 18. The method of claim 1,wherein the -omic data comprises both metatranscriptomic data andphenotypic data.
 19. The method of claim 1, wherein the -omic datacomprises proteomic, which data is used to determine functional activityconditions.
 20. The method of claim 1, wherein the biological conditionsincludes at least one condition selected from the conditions of Table 1.21. The method of claim 1, wherein a plurality of items in the knowledgebase are foods selected from the foods of Table
 2. 22. The method ofclaim 1, wherein a plurality of items in the knowledge base aresupplements selected from the supplements of Table
 3. 23. The method ofclaim 1, wherein a plurality of items in the knowledge base areingredients selected from the compounds of Table
 4. 24. The method ofclaim 1, wherein the desirability ratings for foods comprise a pluralityof ratings hierarchically arranged from least desirable to consume forthe condition to most desirable to consume for the biological condition.25. The method of claim 17, wherein the plurality of desirabilityratings is four ratings, wherein two ratings are undesirable ratings(e.g., “avoid” and “minimize”, one rating is highly desirable (e.g.,“indulge” or “superfood”) and another rating is desirable or neutral(e.g., “enjoy”).
 26. The method of claim 1, wherein the desirabilityratings for supplements or ingredients comprise a positiverecommendation or no recommendation.
 27. The method of claim 1, whereina plurality of the desirability ratings are based on literature sourcesand expert curation.
 28. The method of claim 1, wherein the logicdetermines a final recommendation by prioritizing, first, ratingsindicating a negative effect of the item on a condition, and,prioritizing second, ratings indicating a most beneficial effect of theitem on a condition.
 29. The method of claim 28, wherein the hierarchyof rating, from least to most beneficial, is 1-4, and the priority ofratings to produce a final recommendation for a plurality of the itemsis 1>2>4>3 (e.g., “avoid”>“minimize”>“superfood”>“enjoy”).
 30. Themethod of claim 1, further comprising, determining from the -omic data,a predicted glycemic response by the subject to each of one or moreitems in the knowledge base, which response indicates a glycemicresponse desirability rating; and incorporating the glycemic responsedesirability rating in determining the final recommendation for theitem.
 31. The method of claim 30, wherein the glycemic responsedesirability rating is either positive or negative.
 32. The method ofclaim 1, further comprising, determining whether the subject has asensitivity (i.e., an adverse reaction) for an item; and incorporatingany adverse reaction in determining the final recommendation for theitem.
 33. A method comprising: (a) generating functional activity scoresby: (i) obtaining a gut microbiome sample from a subject; (ii)sequencing nucleic acids from the sample to produce sequence data; (iii)determining from the sequence data, (1) gene (e.g., KEGG Orthology)activity scores; and (2) taxa activity scores; (iv) determining from thegene activity scores and the taxa activity scores, a functional activityscore for each of a plurality of functional categories; (b) optionally,generating a glycemic response score for each of a plurality of fooditems selected from foods, supplements and ingredients by: (i) executinglogic that determines a glycemic response score for a subject based onmacronutrient content of the food and the subject's gene activity scoresand taxa activity scores; (c) optionally, determining food sensitivitiesin the subject; (d) generating phenotype scores by: (i) obtainingphenotype data from the subject; (ii) determining, from the phenotypedata, a phenotype score for each of a plurality of phenotype categories;(d) accessing from computer memory a food database that includes, foreach food item and each sub-optimal functional activity and phenotypestatus, a hierarchical recommendation of the food or supplement; (e)generating an overall hierarchical recommendation for each food orsupplement based on combined recommendations of a food for eachsub-optimal condition present and, optionally, the predicted glycemicresponse and/or food sensitivity to the food or supplement.
 34. A methodcomprising: a) receiving a biological sample from a subject; b)sequencing nucleic acids from biological sample to produce nucleic acidsequence data; c) collecting phenotypic data from the subject; d)determining phenotypic conditions in the subject from the phenotypicdata and functional activity conditions in the subject from the nucleicacid sequence data; e) accessing a knowledge base that includes for eachof a plurality of food items desirability ranking of the food for eachof the phenotypic conditions and functional activity conditions presentin the subject; f) using a recommendation engine, executing logic toproduce a recommendation for each food item for the subject; and f)outputting the food recommendations to an electronic device accessibleby the subject.